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An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.

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[ Daily / Weekly / Overview ]

Nov 23, 2022

Bayesian Modeling / Bayesian Induction

• Theory-based Bayesian models of inductive learning and reasoning - Trends in Cognitive Sciences, 2006. [All Versions]. Josh Tenenbaum's review on Bayesian theory induction.

• How to Grow a Mind: Statistics, Structure, and Abstraction - Science, 2011. [All Versions]. Josh Tenenbaum's review on Bayesian theory induction.

Nov 22, 2022

Metascience / Literature Mining

• Galactica: A Large Language Model for Science - Meta AI, 2022. [All Versions]. A large language model trained on large-scale scientific corpus.

Nov 20, 2022

Meta-Level Considerations / The Aha! Moment

• What Makes an Insight Problem? The Roles of Heuristics, Goal Conception, and Solution Recoding in Knowledge-Lean Problems - Journal of Experimental Psychology, 2004. [All Versions]. [APA].

Nov 17, 2022

Meta-Level Considerations / The Aha! Moment

• A computational model of scientific insight - The nature of creativity: Contemporary psychological perspectives, 1988. [All Versions]. A computational account on insights for scientific discovery.

Nov 15, 2022

Metascience / Science of Science

• The Meaning of "Theory" - Sociological Theory, 2008. [All Versions]. A philosophical account on the definition of "theory" in social science (also can be generalized to natural science).

Nov 14, 2022

Concepts / Theory of Concepts

• The Theory Theory - Mapping the mind: Domain specificity in cognition and culture, Cambridge University Press. [All Versions]. Alison Gopnik's original paper on the theory theory.

Nov 08, 2022

Metascience / Science of Science

• The structure of scientific revolutions - University of Chicago Press: Chicago, 1970. [All Versions]. Thomas Kuhn's original book on the shift of scientific paradigms.

Nov 04, 2022

Methodologies for Experiments / Association Test

• Implicit Association Test - Wikipedia. Wikipedia on the Implicit Association Test, a controversial assessment intended to detect subconscious associations between mental representations of objects (concepts) in memory.

Nov 03, 2022

Others / Commonsense Knowledgebase

• Yanchao Bi - IDG/McGovern Institute for Brain Research and the State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University (BNU), Yanchao Bi's Concept Lab (Bi Lab) - BNU.

Nov 02, 2022

Meta-Level Considerations / The Aha! Moment

• Insight - Wikipedia. Wikipedia on insight.

• Epiphany - Wikipedia. Wikipedia on epiphany, the "feeling" when the Aha! moment comes.

Nov 01, 2022

Metascience / Scientific Writing

• The uses of argument - Cambridge University Press, 1958. [All Versions]. Stephen Toulmin's introduction to the Toulmin argument pattern, which is generally consist of a claim, a justification, and a rebuttal.

• The uses and complexity of argument structures in expert and student persuasive writing - Written Communication, 1998. [All Versions]. A behaviorial study revealing the argument structures exploited by people in argumentative writing.

• Speech Acts of Argumentation: Inference Anchors and Peripheral Cues in Dialogue - AAAI'12, 2012. [All Versions]. The original paper introducing the Information Anchoring Theory (IAT) as an alternate for AIF.

Oct 31, 2022

Metascience / Scientific Writing

• A tagmemic approach to paragraph analysis - College Composition and Communication, 1965. [All Versions]. The original paper on analyzing the structure of expository paragraphs, with the two patterns---the Topic-Restriction-Illustration pattern and the Problem-Solution pattern.

• Towards an argument interchange format - The Knowledge Engineering Review, 2006. [All Versions]. The original paper introducing the Argument Interchange Format (AIF) framework for argumentation analysis.

Oct 30, 2022

Metascience / Science of Science

• The blind men and the elephant: A metaphor to illuminate the role of researchers and reviewers in social science - Methodological Innovations Online, 2013. [All Versions].

Oct 22, 2022

Concepts / Human Concept Representation

• Semantic projection recovers rich human knowledge of multiple object features from word embeddings - Nature Human Behavior, 2022. [All Versions]. Proposing a domain-general method to extract context-dependent relationships from word embeddings: ‘semantic projection’ of word-vectors onto lines that represent multiple dimensions of features, which recovers human judgements across various object categories and properties.

Oct 19, 2022

Metascience / Literature Visualization

• Galex: Exploring the evolution and intersection of disciplines - IEEE Transactions on Visualization and Computer Graphics, 2019. [All Versions].

Oct 18, 2022

Metascience / Literature Visualization

• cite2vec: Citation-Driven Document Exploration via Word Embeddings - IEEE Transactions on Visualization and Computer Graphics, 2016. [All Versions].

Oct 10, 2022

Metascience / Literature Mining

• CORWA: A Citation-Oriented Related Work Annotation Dataset - NAACL'22, 2022. [All Versions].

Oct 07, 2022

Metascience / Science of Science

• Science of Science - Science, 2018. [All Versions]. A comprehensive large-scale review on the science of science.

Oct 03, 2022

Metascience / Science of Science

• Cognitive Science and Science Education - American Psychologist, 1986. [All Versions]. Susan Carey's review on cognitive-science-based methodologies for science education.

Sep 28, 2022

Metascience / Science of Science

• Metascience - Wikipedia.

• Finding Scientific Topics - Proceedings of the National Academy of Sciences, 2004. [All Versions]. Thomas L. Griffiths's analysis of scientific topics using Bayesian model.

• Meta-assessment of Bias in Science - Proceedings of the National Academy of Sciences, 2017. [All Verisions]. An analysis of bias patterns and risk factors in science.

• Slowed Canonical Progress in Large Fields of Science - Proceedings of the National Academy of Sciences, 2021. [All Verisions]. An analysis of why too many papers published each year in a field can lead to stagnation rather than advance.

Sep 24, 2022

Concepts / Human Concept Representation

• Idiosyncratic Tower of Babel: Individual differences in word-meaning representation increase as word abstractness increases - Psychological Science, 2021. [All Versions]. Uncovering the cognitive and neural origins of word-meaning disagreements across individuals.

Methodologies for Experiments / Association Test

• A Meta-Analysis on the Correlation Between the Implicit Association Test and Explicit Self-Report Measures - Personality and Social Psychology Bulletin, 2005. [All Versions].

Sep 21, 2022

Concepts / Human Concept Representation

• Organizing conceptual knowledge in humans with a gridlike code - Science, 2016. [All Versions]. Original findings suggest that global relational codes may be used to organize nonspatial conceptual representations and that these codes may have a hexagonal gridlike pattern when conceptual knowledge is laid out in two continuous dimensions.

Sep 19, 2022

Meta-Level Considerations / The Aha! Moment

• Eureka Effect - Wikipedia. Wikipedia on Eureka effect (a.k.a. Aha! moment, insight, and epiphany), the common human experience of suddenly understanding a previously incomprehensible problem or concept.

Sep 16, 2022

Inductive Logic & Program Synthesis / Commonsense Knowledgebase

• Synthesizing theories of human language with Bayesian program induction - Nature Communications, 2022. [All Versions].

Sep 13, 2022

Bayesian Modeling / Bayesian Induction

• Modeling rules and similarity in colexification - CogSci'21, 2021. [All Versions]. Rule- and similarity-based generalization in colexification.

Methodologies for Experiments / Scaling Up Behavioral Studies

• Scaling up experimental social, behavioral, and economic science - Open Science Foundation Preprints. [All Versions]. A white paper on scaling up social, behavioral, and econimic experiments.

Methodologies for Experiments / Decision Making

• A computational process-tracing method for measuring people’s planning strategies and how they change over time - Behavior Research Methods, 2022. [All Versions]. Model-based strategy identification.

Meta-Level Considerations / Rationality

• Understanding Human Intelligence through Human Limitations - Trends in Cognitive Sciences, 2020. [All Versions]. Tom Griffiths's review on understanding the uniqueness of human intelligence through three aspects of human limitations.

Sep 12, 2022

Meta-Level Considerations / Rationality

• The Adaptive Nature of Human Categorization Behavior - Psychological Review, 1991. [All Versions]. The original paper that relates cognitive resource limitation with Bayesian rational analysis, in the case of categorization behavior.

Sep 11, 2022

Analogy / Scientific Writing

• Similarity involving attributes and relations: Judgments of similarity and difference are not inverses - Psychological Science, 1990. [All Versions].

Sep 07, 2022

Analogy / Scientific Writing

• Visual Analogy: Deep Learning Versus Compositional Models - CogSci'21, 2021. [All Versions]. A human-deep-learning comparison on similarity judgement.

Sep 01, 2022

Bayesian Modeling / Generative Model

• Bayesian Data Analysis - Chapman and Hall/CRC, 1995. [All Versions]. Don Rubin's introductory book on Bayesian models.

Aug 30, 2022

Methodologies for Experiments / Scaling Up Behavioral Studies

• The weirdest people in the world? - Brain and Behavioral Sciences, 2010. [All Versions]. The original paper on rethinking and tackling the sample bias in behaivoral studies, where most subjects are drawn from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies.

Aug 27, 2022

Concepts / Theory of Concepts

• Concepts - Plato Stanford. A collection of the computational philosophical debates about the concepts.

• Theory-theory - Wikipedia. Wikipedia for the Theory theory, a perspective that contextualizes concepts in theoretical (or empirical) systems.

• Words, thoughts, and theories - MIT Press, 1997. [All Versions]. Alison Gopnik's book that articulates and defends the "theory theory" of cognitive and semantic development, the idea that infants and young children, like scientists, learn about the world by forming and revising theories-a view of the origins of knowledge and meaning that has broad implications for cognitive science.

Concepts / AI Concept Representation

• Semantic features of object concepts generated with GPT-3 - 2022. [All Versions]. Testing the semantic attributes of the concepts generated by the large language model GPT-3.

• Unit Testing for Concepts in Neural Networks - Transactions of the Association for Computational Linguistics, 2022. Testing the concept representation by neural networks through Fodor's theory of concepts.

Methodologies for Experiments / Association Test

• Measuring Individual Differences in Implicit Cognition: The Implicit Association Test - Journal of Personality and Social Psychology, 1998. [All Versions]. The original paper introducing the Implicit Association Test.

• Health of the Implicit Association Test at age 3 - Zeitschrift für Experimentelle Psychologie, 2001. [All Versions]. The 3rd year review for the IAT.

• The Implicit Association Test at Age 7: A Methodological and Conceptual Review - Social psychology and the unconscious: The automaticity of higher mental processes (pp. 265–292), Psychology Press, 2007. [All Versions]. The 7th year review for the IAT.

Aug 26, 2022

Paper Writing

• How to write a superb literature review - Nature, 2020. Nature speaks to old hands and first timers about the work they did to make their reviews sing.

Aug 23, 2022

Problem Solving / Human-Level Problem Solving

• The successor representation in human reinforcement learning - Nature Human Behavior, 2017. [All Versions].

Others / Commonsense Knowledgebase

• Yixin Zhu - School of AI and Institute for AI, Peking University (PKU), Cognitive Reasoning Lab (CoRe Lab) - PKU.

• Chaz Firestone - Department of Psychological and Brain Sciences, Johns Hopkins University (JHU), Hopkins Perception & Mind Lab - JHU.

Aug 17, 2022

Courses

• Structure and Interpretation of Computer Programs - MIT. [Book: SICP]. [All Versions]. Classic course on applying structural, procedural, and meta-linguistic abstraction to solve computational problems.

Aug 16, 2022

Causality / Scientific Writing

• Predictive and Diagnostic Learning Within Causal Models: Asymmetries in Cue Competition - Journal of Experimental Psychology, 1992. [All Versions]. Experimental evidences for distincting causality and association.

Aug 12, 2022

Others / Commonsense Knowledgebase

• Mark Ho - Department of Computer Science, Stevens Institute of Technology (SIT).

Aug 10, 2022

Meta-Level Considerations / Meta Learning

• Meta-Q-Learning - ICLR'20, 2020. [All Versions]. The milestone paper on context Meta-RL.

Aug 07, 2022

Knowledge Representation / Commonsense Knowledgebase

• Concepts in a Probabilistic Language of Thought - Center for Brains, Minds, and Machines MEMO No.010, 2014. [All Versions].

Aug 04, 2022

Methodologies for Experiments / Virtual Reality

• How Immersive Is Enough? A Meta-Analysis of the Effect of Immersive Technology on User Presence - Media Psychology, 2016. [All Versions]. A meta-analysis on the extent to which technologies need to be immersive in order to generate a sense of presence.

Aug 01, 2022

Methodologies for Experiments / Quantitative Analysis

• With or Without U? The Appropriate Test for a U-Shaped Relationship - Oxford Bulletin of Economics and Statistics, 2010. [All Versions]. The original method for testing U-shape relation from the data, which is distinctive from the quadratic regression test.

Jul 27, 2022

Paper Writing

• LaTex Configuration - LaTex. LaTex template for configuration file with elegant reference style (gray-colored reference, page backward reference).

• BibTex Template - BibTex. BibTex template for including abbreviations of journals and conferences in AI, Mathematics, and Cognitive Sciences.

Knowledge Management

• Zotero - Digital Scholar. For reference management to manage bibliographic data and research related materials.

Causality / Scientific Writing

• Reasoning with cause and effect - 1998. Judea Pearl's tutorials on causal reasoning with operations on Bayesian networks.

Stanford / Commonsense Knowledgebase

• Li Fei-Fei - Computer Science Department, Human-Centered AI Institute, Stanford, Stanford Vision and Learning Lab - Stanford.

• Noah Goodman - Stanford, Computation & Cognition Lab (CoCoLab) - Department of Psychology, Computer Science Department, Stanford.

• Chelsea Finn - Stanford, Intelligence through Robotic Interaction at Scale (IRIS Group) - Computer Science Department, Stanford.

• Jiajun Wu - Computer Science Department, Stanford.

Harvard / Commonsense Knowledgebase

• Fiery Cushman - Department of Psychology, Harvard, Moral Psychology Research Lab - Harvard.

Jul 26, 2022

Princeton / Commonsense Knowledgebase

• Thomas Griffiths - Princeton, Computational Cognitive Science Lab - Department of Psychology, Department of Computer Science, Princeton.

Jul 23, 2022

Literature Management

• Litmaps - Litmap Ltd. For interactive literature map construction and linked document management.

Knowledge Management

• Where Does Niklas Luhmann's Card Index Come From? - Erudition and the Republic of Letters, 2018. [All Versions]. A simplified introduction on Luhmann's Zettelkasten.

• Niklas Luhmann's Card Index: The Fabrication of Serendipity - Sociologica, 2018. [All Versions].

Cognitive Development / Commonsense Knowledgebase

• Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory - Psychological Bulletin, 2012. [All Versions]. Alison Gopnik's review on the constructivism idea of developmental research.

• Machine Common Sense Concept Paper - DARPA, 2018. [All Versions]. DARPA's perspective on integrating core knowledge from development psychology into machine intelligence systems.

• Cognitive Development - Wikipedia.

• Towards a rational constructivist theory of cognitive development - Psychological Review, 2019. [All Versions]. Fei Xu's review extending Gopnik's view of constructivism, with the rationality as constraint.

• The origins of inquiry: inductive inference and exploration in early childhood - Trends in Cognitive Sciences, 2012. [All Versions]. Laura Schulz's review on children's exploratory play.

• Play, Curiosity, and Cognition - Annual Review of Developmental Psychology, 2020. [All Versions]. Laura Schulz's review on children's exploratory play, which proposes a new perspective on exploratory play to explain the emergence of irrational behaviors in play.

Communications / Language Compositionality

• Word formation supports efficient communication: The case of compounds - CogSci'22, 2022.

Problem Solving / Human-Level Problem Solving

• Learning to act by integrating mental simulations and physical experiments - CogSci'18, 2018. [All Versions]. [Code (⭐1)].

Problem Solving / Planning

• Discovering State and Action Abstractions for Generalized Task and Motion Planning - AAAI'22, 2022. [All Versions].

Problem Solving / Intrinsic Motivation

• Intrinsic Exploration as Empowerment in a Richly Structured Online Game - 2022. [All Versions].

• Multi-task reinforcement learning in humans - Nature Human Behavior, 2021. [All Versions].

Problem Solving / Inverse Reinforcement Learning

• Bayesian Inverse Reinforcement Learning - IJCAI'07, 2007. [All Versions]. A Bayesian account on classic inverse reinforcement learning.

System 1 & System 2 / Dual-Coding Theory

• Mental Representations: A Dual Coding Approach - Oxford University Press, 1990. [All Versions]. The original book on dual coding theory, in the neuroscience account of mental representation.

• Dual coding of knowledge in the human brain - Trends in Cognitive Sciences, 2021. [All Versions]. Yanchao Bi's review on neuroscience experiments on dual coding theory.

• Two Forms of Knowledge Representations in the Human Brain - Neuron, 2020. [All Versions]. Illustrating language-derived and sensory-derived knowledge.

System 1 & System 2 / Neural-Symbolic AI

• Regression Analysis for Interval-Valued Data - Data Analysis, Classification, and Related Methods, 2000. [All Versions]. The original paper on symbolic regression.

• Symbolic data analysis: what is it? - Proceedings in Computational Statistics, 2006. [All Versions].

• DeepProbLog: Neural Probabilistic Logic Programming - NIPS'18, 2018. [All Versions]. The original paper on neuro-symbolic probabilistic programming.

• Learning Explanatory Rules from Noisy Data - Journal of Artificial Intelligence Research, 2018. [All Versions]. The original paper for differential Inductive Logic Programming.

• Bridging Machine Learning and Logical Reasoning by Abductive Learning. - NIPS'19, 2019. [All Versions]. [Slides]. [Code (⭐76)]. The original paper on Abductive Learning, a derivative-free approach for neuro-symbolic learning.

• Learning by Abstraction: The Neural State Machine - NIPS'19, 2019. [All Versions].

• AI Feynman: A physics-inspired method for symbolic regression - Science Advances, 2019. [All Versions]. A general approach for neuro-symbolic formula synthesis.

• Neural Production Systems - ICML'21, 2021. [All Versions]. Yoshua Bengio's perspective on slot attention model as a general production system.

Explainability / Trustworthy AI

• A tale of two explanations: Enhancing human trust by explaining robot behavior - Science Robotics, 2019. [All Versions]. The original paper on human believable robot, a result of the DAPAR-XAI.

• X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust - 2019. [All Versions]. Introducing the idea of AI estimating human users' knowledge in to explainable AI.

Explainability / Strong Machine Learning

• Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP - Machine Learning, 2018. [All Versions]. Stephen Muggleton's account of ultra-strong machine learning, which not only learns human understandable knowledge, but also improves human performance on the corresponding tasks.

• NBDT: Neural-Backed Decision Trees - NIPS'20, 2020. [All Versions]. [code (⭐552)]. Expliciting the decision process of a decision tree through neural networks.

Explainability / Explainable Deep Learning

• Network dissection: Quantifying interpretability of deep visual representations - CVPR'17, 2017. [All Versions]. [Project]. [Dataset: Places365]. The original paper on visualizing the class activation maps to explain convolutional neural networks.

• Understanding the role of Individual Units in a Deep Neural Network - Proceedings of National Academy of Sciences, 2020. [All Versions]. David Bau's review on network dissection for discriminative and generative models.

• Zoom In: An Introduction to Circuits - Distill, 2020. [All Versions]. A perspective on treating neural networks as circuits.

• Compositional Explanations of Neurons - NIPS'20, 2020. [All Versions]. [Project (⭐23)]. A concept-composition version of network dissection.

• Noise or Signal: The Role of Backgrounds in Image Classification - ICLR'21, 2021. [All Versions]. [Project]. A perspective on image background provides strong clue for foreground classification.

• Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation - NIPS'18, 2018. [All Versions]. Maching the learned pattern of neurons in different neural networks.

Embodied Intelligence / Explainable Deep Learning

• Embodied Cognition - Plato Stanford. A computational philosophy account on Embodied Cognition, which emphasizes the significance of an agent's physical body in cognitive abilities.

• Externalism About the Mind - Plato Stanford. A computational philosophy account on mind externalism, a long-term debate about the boundary of embodied intelligence.

• Cognitive engineering: Human problem solving with tools - Human Factors, 1988. [All Versions]. The original idea of investigating huamn tool use in problem solving.

• Tools, language and cognition in human evolution - Cambridge University Press, 1993. [All Versions]. A classic perspective correlating human tool use with the evolution of civilization.

• The Extended Mind - Analysis, 1998. [All Versions]. The original paper on the debate of mind externalism.

• The neural bases of complex tool use in humans - Trends in Cognitive Sciences, 2004. [All Versions]. A neuroscience account of human tool use.

• Spontaneous Metatool Use by New Caledonian Crows - Current Biology, 2007. [All Versions]. A piece of evidence that intelligent animals can take advantage of matatools to make tools for problem solving.

• Tool use and affordance: Manipulation-based versus reasoning-based approaches - Psychological Review, 2016. [All Versions]. A classic review on human tool use and affordance.

• Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition - CVPR'15, 2015. [All Versions]. [Project]. The original paper introducing affordance and physically-grounded tool use into computer vision.

Evolutionary Intelligence / Explainable Deep Learning

• Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space - Science, 2012. [All Versions]. A classic paper correlating biological trade-offs with the evolution of pareto optimality.

• Pareto optimality in multiobjective problems - Applied Mathematics and Optimization, 1977. [All Versions]. The original paper on the pareto optimality in multiobjective problems.

• Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies - IEEE Transactions on Systems, Man, and Cybernetics, 2008. [All Versions]. A comprehensive review on the application of pareto optimality to multiobjective machine learning.

Causality / Scientific Writing

• Identification of Causal Effects Using Instrumental Variables - Journal of the American Statistical Association, 1996. [All Versions].

• Causality - Wikipedia. Wikipedia on causality, which is influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause.

• Causal Models - Plato Stanford. A computational philosophy account on Causal models, which are mathematical models representing causal relationships within an individual system or population.

• Causal Theories of Mental Content - Plato Stanford. A computational philosophy account on causal theories of mental content, which attempts to explain how thoughts can be about things.

• The Seven Tools of Causal Inference, with Reflections on Machine Learning - Communications of the ACM, 2019. [All Versions]. Judea Pearl's review on causal inference in probabilistic graph models.

• Toward Causal Representation Learning - Proceedings of the IEEE, 2021. [All Versions]. Yoshua Bengio's review on the perspective of treating causal inference as a representation learning problem.

• Theory-Based Causal Induction - Psychological Review, 2009. [All Versions]. Thomas Griffiths' review on causal Bayesian theory induction.

• Theory-Based Causal Transfer: Integrating Instance-Level Induction and Abstract-Level Structure Learning - AAAI'20, 2020. [All Versions]. A computatinoal account on causal transfer.

• Causal Reasoning in Rats - Science, 2006. [All Versions]. A piece of evidence for the capability of causal reasoning in intelligent animals.

• Do New Caledonian crows solve physical problems through causal reasoning? - Proceedings of the Royal Society B: Biological Sciences, 2009. [All Versions]. A piece of evidence for the capability of causal reasoning in intelligent animals.

Methodologies for Experiments / Quantitative Analysis

• Experiments with More Than One Random Factor: Designs, Analytic Models, and Statistical Power - Annual Review of Psychology, 2017. [All Versions]. A comprehensive review of the quantitative analysis techniques for behavioral studies.

Methodologies for Experiments / Scaling Up Behavioral Studies

• Scaling up psychology via Scientific Regret Minimization - Proceedings of National Academy of Sciences, 2020. [All Versions]. The statistical and ecological basis for scaling up behavioral studies.

• Using large-scale experiments and machine learning to discover theories of human decision-making - Science, 2021. [All Versions]. A piece of evidence for the merits brought by large-scale behavioral studies in social science.

• Visual Search at Pinterest - KDD'15, 2015. [All Versions]. Large scale user study in the development of the recommendations system by Pinterest.

Methodologies for Experiments / Question Answering

• Searching large hypothesis spaces by asking questions - CogSci'16, 2016. [All Versions]. A behavioral study for the 20 questions game.

• Asking and evaluating natural language questions - CogSci'16, 2016. [All Versions]. A behavioral study for the battleship game.

Methodologies for Experiments / Human-Machine Comparison

• Elimination by aspects: A theory of choice - Psychological Review, 1972. [All Versions]. Herbert Simon's early experiments on computer aided behavioral studies.

Methodologies for Experiments / Virtual Reality

• Virtual reality in behavioral neuroscience and beyond - Nature Neuroscience, 2002. [All Versions]. A classic review on the early applications of Virtual Reality to behavioral studies.

• The psychology of virtual reality - The psychology of technology: Social science research in the age of Big Data (pp. 155–193), American Psychological Association, 2022. [All Versions]. Jeremy Bailenson's review on the applications of Virtual Reality to behavioral studies.

Meta-Level Considerations / Meta Learning

• Automated Reinforcement Learning (AutoRL): A Survey and Open Problems - 2022. [All Versions]. A comprehensive review on AutoRL.

• Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks - ICML'17, 2017. [All Versions]. Chelsea Finn's original paper on Model-Agnostic Meta-Learning (MAML).

• Bayesian Model-Agnostic Meta-Learning - NIPS'18, 2018. [All Versions]. A Bayesian account on MAML.

David Marr / Commonsense Knowledgebase

• Vision: A Computational Investigation into the Human Representation and Processing of Visual Information - MIT Press, 1982. [All Versions].

Meta-Level Considerations / Marr's Levels of Analysis

• Bridging Levels of Analysis for Probabilistic Models of Cognition - Current Directions in Psychological Science, 2012. [All Versions]. A Marr's paradigm account on probabilistic models.

• Levels of Analysis in Computational Social Science - CogSci'18, 2018. [All Versions]. A Marr's paradigm account on computational social science.

• Levels of Analysis for Machine Learning - ICLR'20 Bridging AI and Cognitive Science Workshop, 2020. [All Versions]. A Marr's paradigm account on machine learning.

Meta-Level Considerations / Gestalt

• Gestalt theory - A source book of Gestalt psychology, 1938. [All Versions]. The original book on Gestalt psychology.

• Gestalt Psychology - Psychologische Forschung, 1967. [All Versions]. Wolfgang Köhler's review on Gestalt psychology.

• Deep Learning: How the Mind Overrides Experience - Cambridge University Press, 2011. [All Versions].

Meta-Level Considerations / Rationality

• Bounded Rationality - Plato Stanford. A computational philosophy account on Bounded Rationality, an elementary hypothesis of human intelligence in psychology and ecology.

• Instrumental Rationality - Plato Stanford. A computational philosophy account on Instrumental Rationality, a dabate on whether an agent's decision is made intentionally or out of rational coherence.

• Computational rationality: A converging paradigm for intelligence in brains, minds, and machines - Science, 2015. [All Versions]. A comprehensive review on the rationality of Bayesian computational models.

• Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources - Behavioral and Brain Sciences, 2020. [All Versions]. A resource-rational account on interpreting human intelligence.

Meta-Level Considerations / Cognitive Architecture

• The secret life of predictive brains: what's spontaneous activity for? - Trends in Cognitive Sciences, 2021. [All Versions]. A neuroscience account on brain as a generative model.

• Is human cognition adaptive? - Behavioral and Brain Sciences, 1991. [All Versions]. The original paper introducing the adaptation perspective of human intelligence, the theoretical basis of the ACT cognitive architecture.

• What is consciousness, and could machines have it? - Science, 2017. [All Versions]. A perspective on the two levels of consciousness in machine intelligence.

Theory of Mind / Scientific Writing

• Theory of Mind - Wikipedia. Wikipedia on Theory of Mind (ToM), a cognitive capability that estimating others' goal, belief, and desire.

• The Computational Theory of Mind - Plato Stanford. A computational philosophy account on ToM.

• Action Understanding as Inverse Planning - Cognition, 2009. [All Versions]. [Appendix]. The original paper on Inverse Planning, a computational implementation of ToM.

• Bayesian Theory of Mind: Modeling Joint Belief-Desire Attribution - CogSci'11, 2011. [All Versions].

• Bayesian Theory of Mind : modeling human reasoning about beliefs, desires, goals, and social relations - Ph.D. Dissertation MIT, 2012. [All Versions]. Chris Baker's Ph.D. dissertation, a comprehensive review on Bayesian modeling of Theory of Mind.

• Bayesian Brains without Probabilities - Trends in Cognitive Sciences, 2016. [All Versions]. A perspective on human probabilistic modeling without explicit probabilistic computation.

• AGENT: A Benchmark for Core Psychological Reasoning - ICML'21, 2021. [All Versions]. A benchmark for AI that modeling the core knowledge of ToM.

• Experimental Games and Social Decision Making - Annual Review of Psychology, 2021. [All Versions]. A comprehensive review on social ToM experiment pafadigms.

• Theory of Minds: Understanding Behavior in Groups through Inverse Planning - AAAI'19, 2019. [All Versions]. Inverse Planning in multi-agent setting.

• Using human brain activity to guide machine learning - Scientific Report, 2018. [All Versions].

• Learning Triadic Belief Dynamics in Nonverbal Communication from Videos - CVPR'21, 2021. [All Versions]. Theory of Mind in the perception level, introduced as a computer vision task.

• Ten-month-old infants infer the value of goals from the costs of actions - Science, 2017. [All Versions]. A piece of evidence for children's capability on ToM.

• Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others - NIPS'21, 2021. [All Versions].

• Intentonomy: a Dataset and Study towards Human Intent Understanding - CVPR'21, 2021. [All Versions]. A large-scale database on human intentionally-posted images on social media.

• Adventures in Flatland: Perceiving Social Interactions Under Physical Dynamics - CogSci'20, 2020. [All Versions].

Analogy / Scientific Writing

• Metaphor - Plato Stanford. A computational philosophy account on Metaphor, a poetically or rhetorically ambitious use of words, a figurative as opposed to literal use.

• Analogy and Analogical Reasoning - Plato Stanford. A computational philosophy account on Analogy, a comparison between two objects, or systems of objects, that highlights respects in which they are thought to be similar.

• A Cognitive Theory of Metaphor - MIT Press, 1985. [All Versions]. A cognitive account on Metaphor.

• The structure-mapping engine: Algorithm and examples - Artificial Intelligence, 1989. [All Versions]. A computational implementation of analogy.

• Structure mapping in analogy and similarity - American Psychologist, 1997. [All Versions]. A perspective unifying analogy and similarity judgement.

• A theory of relation learning and cross-domain generalization - Psychological Review, 2022. [All Versions]. A comprehensive review on the perspective of treating analogy as cross-domain generalization.

• Emergence of analogy from relation learning - Proceedings of National Academy of Sciences, 2019. [All Versions]. Analogy feature in language models.

• Analogies Explained: Towards Understanding Word Embeddings - ICML'19, 2019. [All Versions]. Explaining the analogy capability in word embeddings.

• Analogy-preserving Semantic Embedding for Visual Object Categorization - ICML'13, 2013. [All Versions]. The first application of analogy to machine learning.

• Analogy between concepts - Artificial Intelligence, 2019. [All Versions]. A mathematical account on analogy.

• Preschoolers and adults make inferences from novel metaphors - CogSci'22, 2022. [All Versions]. A piece of evidence that understanding metaphors is capable for different cognitive development phases.

Commonsense / Intuitive Physics

• Intuitive Physics: Current Research and Controversies - Trends in Cognitive Sciences, 2018. [All Versions]. Hongjing Lu's review on intuitive physics.

• Simulation as an engine of physical scene understanding - Proceedings of National Academy of Sciences, 2013. [All Versions]. [Appendix]. The first attempt to computationally simulate intuitive physics.

• Functional neuroanatomy of intuitive physical inference - Proceedings of National Academy of Sciences, 2016. [All Versions]. A piece of evidence for the functional part of intuitive physics in human brain.

• Mind Games: Game Engines as an Architecture for Intuitive Physics - Trends in Cognitive Sciences, 2017. [All Versions]. Tomer Ullman's review on simulation-based intuitive physics.

• Limits on Simulation Approaches in Intuitive Physics - Cognitive Psychology, 2021. [All Versions]. Ernest Davis's perspective against intuitive physics, that physcial reasoning is logical reasoning instead of intuition.

Commonsense / AI Commonsense Reasoning

• Representations of Commonsense Knowledge - Morgan Kaufmann, 1990. [All Versions]. A classic book on commonsense knowledge.

• Towards a theory of commonsense visual reasoning - FSTTCS, 1990. [All Versions]. The original paper on visual commonsense.

• Commonsense reasoning and commonsense knowledge in artificial intelligence - Communications of the ACM, 2015. [All Versions]. Gary Marcus's review on commonsense knowledge in AI.

• Abductive Commonsense Reasoning - ICLR'20, 2020. [All Versions]. Abductive commonsense reasoning on large language models.

• Experience Grounds Language - EMNLP'20, 2020. [All Versions]. A perspective on the furture of computational linguistics research---commonsense-driven and embodied language.

Commonsense / Commonsense Knowledgebase

• CYC: A Large-Scale Investment in Knowledge Infrastructure - Communications of the ACM, 1995. [All Versions]. The first attempt to build large-scale commonse knoweldgebase from human knowledge.

• The Public Acquisition of Commonsense Knowledge - Proceedings of AAAI Spring Symposium on Acquiring (and Using) Linguistic (and World) Knowledge for Information Access, 2002. [All Versions]. The first attempt for acquring commonsense knowlege from humans' activities on the internet.

Inductive Logic & Program Synthesis / Commonsense Knowledgebase

• Inductive Logic - Plato Stanford. A computational philosophy account on Inductive Logic, which is a logic of evidential support.

• First-order Model Theory - Plato Stanford. A computational philosophy account on First-order Model Theory, which is a branch of mathematics that deals with the relationships between descriptions in first-order languages and the structures that satisfy these descriptions.

• Paraconsistent Logic - Plato Stanford. A computational philosophy account on Paraconsistent Logic, where any logic is paraconsistent as long as it is not explosive.

• Logical Consequence - Plato Stanford. A computational philosophy account on Logical Consequence, which is about the relation between premises and conclusions in valid arguments.

• Logic Pluralism - Plato Stanford. A computational philosophy account on Logic Pluralism, which is the view that there is more than one correct logic.

• The Emergence of First-Order Logic - Plato Stanford. A computational philosophy account on the emergence of first-order logic, mainly about first-order logic is natural retrospect.

• Second-order and Higher-order Logic - Plato Stanford.

• Program Synthesis - Foundations and Trends in Programming Languages, 2017. [All Versions]. Sumit Gulwani's comprehensive review on program synthesis.

• The Discovery of the Equator or Concept Driven Learning - IJCAI'83, 1983. [All Versions]. The original paper on second-order metarules.

• Meta-interpretive learning: application to grammatical inference - Machine Learning, 2014. [All Versions]. Stephen Muggleton's original paper on Meta-Interpretive Learning (MIL).

• Inductive logic programming at 30: a new introduction - Journal of Artificial Intelligence Research, 2020. [All Versions]. A 30-year comprehensive review on Inductive Logic Programming.

• Qualitative choice logic - Artificial Intelligence, 2004. [All Versions].

• DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning - 2020. [All Versions]. A incremental learning version of Bayesian program learning.

Knowledge Representation / Commonsense Knowledgebase

• Handbook of Knowledge Representation - Elsevier, 2008. [All Versions]. A pragmatical handbook for all kinds of knowledge representation modes.

• Logic and Ontology - Plato Stanford. A computational philosophy account on logic and ontology, mainly about the intersections of logic and ontology in many significant philosophy problems.

• The Language of Thought Hypothesis - Plato Stanford. A computational philosophy account on the laugnage of though hypothesis, which proposes that thinking occurs in a mental language.

• Scientific Representation - Plato Stanford. A computational philosophy account on scientific representation, focusing on how scientific models represent their target systems.

• Self-Knowledge - Plato Stanford. A computational philosophy account on self-knowledge, which standardly refers to knowledge of one's own mental states—that is, of what one is feeling or thinking, or what one believes or desires.

• Supervenience - Plato Stanford. A computational philosophy account on supervenience, where a set of properties A supervenes upon another set B just in case no two things can differ with respect to A-properties without also differing with respect to their B-properties.

• Dialogical Logic - Plato Stanford. A computational philosophy account on dialogical logic, which is a dialogue-based approach to logic and argumentation rooted in a research tradition that goes back to dialectics in Greek Antiquity, when problems were approached through dialogues in which opposing parties discussed a thesis through questions and answers.

• Temporal Logic - Plato Stanford.

• Situation Calculus - Wikipedia. Wikipedia on Situation Calculus, which is a logic formalism designed for representing and reasoning about dynamical domains.

• Modal Logic - Plato Stanford. A computational philosophy account on Modal Logic, which is the study of the deductive behavior of the expressions 'it is necessary that' and 'it is possible that'.

• Epistemic Logic - Plato Stanford. A computational philosophy account on Epistemic Logic, which is a subfield of epistemology concerned with logical approaches to knowledge, belief and related notions.

• The Perception of Relations - Trends in Cognitive Sciences, 2021. [All Versions]. Chaz Firestone's review on the perception of relation, in constrast to the conventional reasoning view.

• Qualitative Simulation - Artificial Intelligence, 1986. [All Versions]. Benjamin Kuipers' original paper on qualitative reasoning.

• Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge - MIT Press, 1994. [All Versions]. Benjamin Kuipers' comprehensive book on qualitative reasoning.

• Answer Set Programming - ICLPNR'99, 1999. [All Versions]. The original paper on Answer Set Programming (ASP).

• Action Languages, Answer Sets, and Planning - The Logic Programming Paradigms, 1999. [All Versions].

• The discovery of structural form - Proceedings of National Academy of Sciences, 2008. [All Versions]. Chales Kemp's review on theory induction.

• Theory Acquisition and the Language of Thought - CogSci'08, 2008. [All Versions].

• Biocoder: A programming language for standardizing and automating biology protocols - Journal of Biological Engineering, 2010. [All Versions]. Microsoft's programming language for representing biology protocols.

Learning in the Open World / Commonsense Knowledgebase

• Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly - IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. [All Versions]. A comprehensive review on zero-shot learning.

• Generalizing from a few examples: A survey on few-shot learning - ACM Computing Survey, 2020. [All Versions].

• Towards Open World Recognition - CVPR'15, 2015. [All Versions]. The first paper introducing the problem of open-world recognition.

• In the Wild: From ML Models to Pragmatic ML Systems - ICLR'20, 2020. [All Versions]. A comprehensive review on incremental machine learning.

Jul 22, 2022

Paper Reading

• How to Read a Paper - ACM SIGCOMM Computer Communication Review, 2007. [All Versions]. A comprehensive tutorial on reading scientific papers.

Literature Management

• Construction of the Literature Graph in Semantic Scholar - NAACL'18, 2018. [All Versions]. Semantic Scholar with extracting feature and metadata from raw paper data.

• S2ORC: The Semantic Scholar Open Research Corpus - ACL'20, 2020. [All Versions]. An open corpus of academic papers released by Semantic Scholar.

• StateOfTheArt.AI - StateOfTheArtAI. For tracking, collecting and visualizing the development of AI research.

Knowledge Management

• Knowledge organization - Wikipedia. Wikipedia on knowledge organization methods.

• Zettelkasten - Wikipedia. Wikipedia on the Zettelkasten method.

• Roam Research - Roam Research. For linked document management, visualization, and sharing.

• Foam - Foambubble. For linked document management, visualization, and sharing, opensourced softward built on VSCode.

• Building a Second Brain - Forte Labs, LLC. Connecting ideas in graphs.

Abduction / Explanation

• Abduction - Plato Stanford. A computational philosophy account on Abduction, one of the three thinking patterns besides Induction and Deduction, being unique for its potential to introduce new ideas into current knowledge.

• Scientific Explanation - Plato Stanford. A computational philosophy account on Scientific Explanation, a canonical application of Abduction.

• Scientific Reduction - Plato Stanford. A computational philosophy account on Scientific Reduction, which comes with no explicit boundary with Explanation.

• Non-monotonic Logic - Plato Stanford. A computational philosophy account on Non-monotonic Logic, a family of formal frameworks devised to capture and represent defeasible inference.

• Philosophical Writings of Peirce - Courier Corporation, 1955. [All Versions]. Original writings by C. S. Peirce, the establisher of Abduction.

• The Inference to the Best Explanation - Philosophical Review, 1965. [All Versions]. Lipton's original paper on Inference to the Best Explanation as a special case of Abduction.

• Inference to the Best Explanation - Routledge, 1991. [All Versions]. Lipton's book on Inference to the Best Explanation as a special case of Abduction.

• A Study of Thinking - Routledge, 1956. [All Versions]. A classic book on thinking patterns.

• Abductive Reasoning and Learning - Springer, 2000. [All Versions]. An introductory account on abductive reasoning.

• Abductive Reasoning: Logical Investigations into Discovery and Explanation - Springer, 2006. [All Versions]. An introductory account on abductive reasoning.

• Explanation and Abductive Inference - The Oxford Handbook of Thinking and Reasoning, 2012. [All Versions]. A handbook on the formulations of Abduction.

• Probabilistic models of cognition: Conceptual foundations - Trends in Cognitive Sciences, 2006. [All Versions]. A Bayesian account of Abduction.

• The structure and function of explanations - Trends in Cognitive Sciences, 2006. [All Versions]. Basic computation modes of Abduction.

• Explanatory Preferences Shape Learning and Inference - Trends in Cognitive Sciences, 2016. [All Versions]. An account showing that inductive bias is critical for explanation.

• Explanation, updating, and accuracy - Journal of Cognitive Psychology, 2016. [All Versions].

• Best, second-best, and good-enough explanations: How they matter to reasoning - Journal of Experimental Psychology, 2018. [All Versions]. A subjective probability account of Abduction.

• How explanation guides belief change - Trends in Cognitive Sciences, 2021. [All Versions]. A review on the subjective probability account of Abduction.

• Patterns of abduction - Synthese, 2007. [All Versions]. A categorization for Abduction in the account of pure philosophy.

• On the distinction between Peirce's abduction and Lipton's Inference to the best explanation - Synthese, 2011. [All Versions].

• Probabilistic alternatives to Bayesianism: the case of explanationism - Frontiers in Psychology, 2015. [All Versions]. A non-Bayesian account of Abduction.

• A Probabilistic Theory of Abductive Reasoning - ICAART, 2021. [All Versions]. A probabilistic perspective for interpreting Abductive Reasoning.

• Abduction, Induction, and Analogy - Model-Based Reasoning in Science and Technology, 2010. [All Versions]. The distinctions and relations between Abduction, Induction, and Analogy.

• Remembrance of inferences past: Amortization in human hypothesis generation - Cognition, 2018. [All Versions]. A rational account of human hypothesis generation.

• Explanation-seeking curiosity in childhood - Current Opinion in Behavioral Sciences, 2020. [All Versions]. A piece of developmental pshchological evidence for Abduction in young children.

Abduction / Scientific Discovery

• Scientific Discovery - Plato Stanford. A computational philosophy account on Scientific Discovery, the process or product of successful scientific inquiry, sometimes an Abduction-like (Explanation) thinking pattern.

• Models of Discovery: And Other Topics in the Methods of Science - Springer, 1977. [All Versions]. The original book on search as scientific thinking.

• Scientific discovery: Computational explorations of the creative processes - MIT Press, 1987. [All Versions]. A computational account unifying Scientific Discovery with the creativity feature of Abduction.

• Induction: Processes of Inference, Learning, and Discovery - MIT Press, 1989. [All Versions]. An Induction account of Scientific Discovery.

• Dual Space Search During Scientific Reasoning - Cognitive Science, 1988. [All Versions]. The original paper on the dual space search as scientific thinking theory.

• Complexity Management in a Discovery Task - CogSci'92, 1992. [All Versions]. Advanced experiments on dual space search.

• A dual-space model of iteratively deepening exploratory learning - International Journal of Human-Computer Studies, 1996. [All Versions]. Iterative version (in depth and in width) of dual space search.

• Heuristics for Scientific Experimentation: A Developmental Study - Cognitive Psychology, 1993. [All Versions]. A piece of evidence on children have basic scientific thinking skills.

• A 4-Space Model of Scientific Discovery - CogSci'95, 1995. [All Versions]. Extending the dual space search.

• When to trust the data: Further investigations of system error in a scientific reasoning task - Memory & Cognition, 1996. [All Versions]. A behavioral account on the shift between bottom-up observation and top-down reasoning.

• Confirmation, disconfirmation, and information in hypothesis testing - Psychological Review, 1987. [All Versions]. A psychological account on hypothesis testing.

• Children and adults as intuitive scientists - Psychological Review, 1989. [All Versions]. A perspective against search as scientific thinking.

• Abduction and styles of scientific thinking - Synthese, 2021. [All Versions]. A computational philosophy account connecting Abduction and scientific thinking.

Abduction / Rationalization

• Imagination and the generation of new ideas - Cognitive Development, 2015. [All Versions]. A piece of evidence for rationalization in childhood.

• Coalescing the Vapors of Human Experience into a Viable and Meaningful Comprehension - CogSci'16, 2016. [All Versions]. Constrainted thinking as rationalization.

• How We Know What Not To Think - Trends in Cognitive Sciences, 2019. [All Versions]. A comprehensive review on rationalization.

• Rationalization is rational - Behavioral and Brain Sciences, 2020. [All Versions]. A rationality account on rationalization.

• Why Imaginary Worlds? The psychological foundations and cultural evolution of fictions with imaginary worlds - Behavioral and Brain Sciences, 2021. [All Versions]. A review of rationalization as imaginary worlds in fictions.

Abduction / Applications in AI

• Functional genomic hypothesis generation and experimentation by a robot scientist - Nature, 2004. [All Versions]. A canonical application of logical abduction on biodesign.

• Highly accurate protein structure prediction with AlphaFold - Nature, 2021. [All Versions]. A canonical application of observation- and explanation- based method for protein structure prediction instead of first-principle-based methods.

• Interpretation as abduction - Artificial Intelligence, 1993. [All Versions]. A computational account on interpretation as Abduction.

• Probabilistic Horn abduction and Bayesian networks - Artificial Intelligence, 1993. [All Versions]. Casual abduction in Bayesian networks.

• Abductive Logic Programming - Journal of Logic Computation, 1992. [All Versions]. The original paper in ALP.

• ACLP: Abductive Constraint Logic Programming - The Journal of Logic Programming, 1999. [All Versions]. The original paper in ACLP.

• Abduction in Logic Programming - Computational Logic, 2002. [All Versions]. The revised version of the ALP paper.

• Machine Translation Using Abductive Inference - COLING, 1990. [All Versions]. An application of abduction in language translating.

• Anomaly detection through explanations - Ph.D Dissertation MIT, 2018. [All Versions]. An application of abduction in anomaly detection.

Bayesian Modeling / Bayesian Induction

• Bayesian Epistemology - Plato Stanford. A computational philosophy account on the nature of uncertainty modeling in Bayesian Epistemology.

• Probabilistic machine learning and artificial intelligence - Nature, 2015. [All Versions]. Zoubin Ghahramani's review on Bayesian machine learning.

• Generalization, similarity, and Bayesian inference - Behavioral and Brain Sciences, 2001. [All Versions]. Josh Tenenbaum's review on Bayesian generalization.

• Bayesian modeling of human concept learning - NIPS'98, 1998. [All Versions]. Original paper on Bayesian generalization.

• Rules and Similarity in Concept Learning - NIPS'99, 1999. [All Versions]. Unifying rule-based and similarity-based generalization via Bayesian generalization.

• Word learning as Bayesian inference - Psychological Review, 2007. [All Versions]. [APA]. Fei Xu's review on Bayesian word learning.

• Human-level concept learning through probabilistic program induction. - Science, 2015. [All Versions]. [Supplementary Material]. Bayesian program induction for few-shot learning.

• Building Machines That Learn and Think Like People - Behavioral and Brain Sciences, 2017. [All Versions]. Brenden Lake and Josh Tenenbaum's review on Bayesian modeling.

Bayesian Modeling / Generative Model

• Filters, random fields and maximum entropy (FRAME): Towards a unified theory for texture modeling - International Journal of Computer Vision, 1998. [All Versions]. Song-Chun Zhu's original paper on energy-based generative texture modeling.

• Object Perception as Bayesian Inference - Annual Review of Psychology, 2004. [All Versions]. Alan Yuille's review on Bayesian object perception.

• A tale of three probabilistic families: Discriminative, descriptive, and generative models - Quarterly of Applied Mathematics, 2018. [All Versions]. Ying Nian Wu's review on three families of statistical modeling.

• From information scaling of natural images to regimes of statistical models - Quarterly of Applied Mathematics, 2008. [All Versions]. A statistical account for the shift from textons to texture.

• A Theory of Generative ConvNet - ICML'16, 2016. [All Versions].

• Learning Latent Space Energy-Based Prior Model - NIPS'20, 2020. [All Versions]. [Project]. [Code (⭐26)]. A milestone paper on Latent Energy-Based Model.

• Image segmentation by data-driven markov chain monte carlo - IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002. [All Versions]. Classic method for image segmentation via generative modeling.

• A Tutorial on Energy-Based Learning - Predicting Structured Data, MIT Press, 2006. [All Versiosn]. Yann LeCun's tutorial on energy-based learning.

• Analysis of Langevin Monte Carlo via Convex Optimization - Journal of Machine Learning Research, 2019. [All Versions].

• Where do hypotheses come from? - Cognitive Psychology, 2017. [All Versions]. A Bayesian account for modeling basic rules as the hypothesis space.

Bayesian Modeling / Nonparametric Model

• A Bayesian Analysis of Some Non-parametric Problems - The Annals of Statistics, 1973. [All Versions]. A classic review on non-parametric problems.

• Mixtures of Dirichlet Process with Applications to Bayesian Nonparametric Problems - The Annals of Statistics, 1974. [All Versions]. The original paper on Dirichlet Process modeling for non-parametric problems.

• Latent Semantic Indexing: A Probabilistic Analysis - Journal of Computer and System Sciences, 2000. [All Versions]. The original paper on hierarchical topic model.

• Finding scientific topics - Proceedings of the National Academy of Sciences, 2004. [All Versions]. Application on scientific paper ananlysis for hierarchical topic model.

• Hierarchical topic models and the nested Chinese restaurant process - NIPS'03, 2003. [All Versions]. The original paper for nested Chinese restaurant process.

• Infinite Latent Feature Models and the Indian Buffet Process - Gatsby Computational Neuroscience Unit Technical Report 2005-001, 2005. [All Versions].

• The Indian Buffet Process: An Introduction and Review - Journal of Machine Learning Research, 2011. [All Versions]. Tom Griffiths and Zoubin Ghahramani's review on infinite models, including the Chinese Restaurant Process (CRP) and the Indian Buffet Process (IBP).

• Nonparametric Bayesian Logic - UAI'05, 2005. [All Versions]. The first paper integrating logic into non-parametric model.

• Statistical Predicate Invention - ICML'07, 2007. [All Versions]. Treating predicate invention as a non-parametric problem, in the account of statistics.

Bayesian Modeling / Bayesian Optimization

• A Tutorial on Bayesian Optimization - 2018. [All Versions].

• Practical Bayesian Optimization of Machine Learning Algorithms - NIPS'12, 2012. [All Versions]. The original paper for applying Bayesian optimization to machine learning hyperparameter selection.

Complexity & Information Theory / Theory

• An introduction to Kolmogorov complexity and its applications - Springer, 2008. [All Versions]. The introductory book for Algorithmic Information Theory, especially the Kolmogorov complexity theory.

• Complexity and the representation of patterned sequences of symbols - Psychological Review, 1972. [All Versions]. Herbert Simon's review on subjective complexity.

• Algorithmic Information Theory - IBM Journal of Research and Development, 1977. [All Versions]. Chaitin's original paper on Algorithmic Information Theory.

Complexity & Information Theory / Dimensionality Reduction

• A global geometric framework for nonlinear dimensionality reduction - Science, 2000. [All Versions]. The original paper on spectrum clustering.

• Reducing the dimensionality of data with neural networks - Science, 2006. [All Versions]. The original paper on Variational Autoencoder.

• Representation Learning: A Review and New Perspectives - IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013. [All Versions]. Yoshua Bengio's review on representation learning.

• Representation Learning: A Statistical Perspective - Annual Review of Statistics and Its Application, 2020. [All Versions]. Song-Chun Zhu and Ying Nian Wu's review on representation learning, in an account of statistics.

• Deep Learning and the Information Bottleneck Principle - IEEE Information Theory Workshop'15, 2015. [All Versions]. The first paper identifying the problem of information bottleneck in representation learning.

• On the information bottleneck theory of deep learning - Journal of Statistical Mechanics: Theory and Experiment, 2019. [All Versions].

Complexity & Information Theory / Visual Complexity

• Visual complexity: a review - Psychological Bulletin, 2006. [All Versions]. [APA]. A psychological account on visual complexity.

• Seeing and speaking: How verbal “description length” encodes visual complexity - Journal of Experimental Psychology, 2022. [All Versions]. [APA]. Empirical evidencs showing the relation between visual complexity and description length.

• How variability shapes learning and generalization - Trends in Cognitive Sciences, 2022. [All Versions]. A comprehensive review on the trade-off between variability and generalization ability.

Communications / Visual Communication

• The Interactive Evolution of Human Communication Systems - Cognitive Science, 2010. [All Versions]. Nicolas Fay's original paper on iconicity.

• Iconicity: From sign to system in human communication and language - Pragmatics & Cognition, 2014. [All Versions]. Nicolas Fay's account on the emergence of iconic language.

• Graphical Language Games: Interactional Constraints on Representational Form - Cognitive Science, 2007. [All Versions]. The first paper introducing the graphical language game.

• Pixelor: A Competitive Sketching AI Agent. So you think you can beat me? - ACM SIG Graph, 2020. [All Versions]. [Project]. Rationality in feature sketching.

• Pragmatic Inference and Visual Abstraction Enable Contextual Flexibility During Visual Communication - Computational Brain & Behavior, 2020. [All Versions]. A computational account on the rational behavior in graphical language games.

• Emergent Graphical Conventions in a Visual Communication Game - 2021. [All Versions]. A computational account on the emergence of iconic language.

• Communicating artificial neural networks develop efficient color-naming systems - Proceedings of National Academy of Sciences, 2021. [All Versions]. Simulating the emergence of code as the communication bottleneck in color learning task.

• Bridging cultural and cognitive perspectives on similarity reasoning - CogSci'22, 2022. [All Versions].

Communications / Pragmatics

• Pragmatics - Plato Stanford. A computational philosophy account of Pragmatics, whilch studies utterances in specific contexts.

• Predicting Pragmatic Reasoning in Language Games - Science, 2012. [All Versions]. The original paper on Rational Speech Act (RSA).

• Pragmatic Language Interpretation as Probabilistic Inference - Trends in Cognitive Sciences, 2016. [All Versions]. Noah Goodman and Micheal Frank's review on Rational Speech Act.

• Processing gradable adjectives in context: A visual world study - Semantics and Linguistic Theory, 2016. [All Versions]. Adjective understanding as a rational inference in the context.

• Social Pragmatics: Preschoolers Rely on Commonsense Psychology to Resolve Referential Underspecification - Child Development, 2019. [All Versions]. A piece of evidence for children's capability on social pragmatics.

• Pragmatic Issue-Sensitive Image Captioning - ACL Findings: EMNLP'20, 2020. [All Versions]. Application of Rational Speech Act to Image Captioning.

• Disentangling contributions of visual information and interaction history in the formation of graphical conventions - CogSci'19, 2019. [All Versions].

Communications / Pointing & Pantomime

• Twelve-month-olds communicate helpfully and appropriately for knowledgeable and ignorant partners - Cognition, 2008. [All Versions]. The original paper on child pointing.

Communications / Language Compositionality

• Compositionality - Plato Stanford. A computational philosophy account on compositionality, one of the distinctive feature of language.

• The Principle of Semantic Compositionality - Topoi, 1994. [All Versions]. The original paper on the principle of semantic compositionality.

• On The Emergence Of Compositionality - Proceedings of the Evolution of Language Conference'06, 2006. [All Versions]. The original paper on the emergence of compositionality.

• Multi-Agent Cooperation and the Emergence of (Natural) Language - ICLR'17, 2017. [All Versions]. The original paper on the emergence of language in multi-agent reinforcement learning.

Problem Solving / Human-Level Problem Solving

• Elements of a theory of human problem solving - Psychological Review, 1958. [All Versions]. Herbert Simon's original idea on human problem solving.

• Human Problem Solving - Englewood Cliffs, NJ: Prentice-hall, 1972. [All Versions]. Herbert Simon's classic idea of human problem solving as search.

• Judgment under Uncertainty: Heuristics and Biases: Biases in judgments reveal some heuristics of thinking under uncertainty - Science, 1974. [All Versions]. Daniel Kahneman's classic idea of prospective theory.

• Computational evidence for hierarchically structured reinforcement learning in humans - Proceedings of National Academy of Sciences, 2020. [All Versions]. A piece of evidence on hierarchical human planning.

• People construct simplified mental representations to plan - Nature, 2022. [All Versions]. A computational account on rational problem representation in human planning.

• Rapid trail-and-error learning with simulation supports flexible tool use and physical reasoning. - Proceedings of National Academy of Sciences, 2020. [All Versions]. [Project]. [Appendix]. A computational account on rapid trail-and-error problem solving with a noisy prior model.

• Insightful problem solving and creative tool modification by captive nontool-using rooks - Proceedings of National Academy of Sciences, 2009. [All Versions]. [Supplementary Material]. A piece of evidence on creative tool use in intelligent animals.

Problem Solving / Planning

• From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning - Journal of Artificial Intelligence Research, 2018. [All Versions]. Leslie Kaelbling's review on hierarchical Task-and-Motion-Planning (hierarchical TAMP).

• Integrated Task and Motion Planning - Annual Review of Control, Robotics, and Autonomous Systems, 2021. [All Versions]. Leslie Kaelbling's review on Task-and-Motion-Planning (TAMP).

• Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Robotics: Science and Systems, 2018. [All Versions].

Problem Solving / Intrinsic Motivation

• Intrinsically Motivated Reinforcement Learning - NIPS'04, 2004. [All Versions]. A comprehensive review on intrinsic reward functions in classic reinforcement learning.

• Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study - Journal of Artificial Intelligence Research, 2020. [All Versions].

• Curiosity-driven Exploration by Self-supervised Prediction - ICML'17, 2017. [All Versions]. The original paper on curiosity as intrinsic motivation.

• UCB Exploration via Q-Ensembles - 2017. [All Versions].

• Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning - NIPS'15, 2015. [All Versions]. The original paper on empowerment as intrinsic motivation.

Problem Solving / Reinforcement Learning

• Reinforcement learning: An introduction - MIT Press, 2018. [All Versions]. Richard Sutton's comprehensive book on reinforcement learning.

• Reinforcement learning: A survey - Journal of Artificial Intelligence Research, 1996. [All Versions]. Leslie Kaelbling's review on reinforcement learning.

• Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning - Artificial Intelligence, 1999. [All Versions]. The original paper on operation reinforcement learning.

• On Monte Carlo Tree Search and Reinforcement Learning - Journal of Artificial Intelligence Research, 2017. [All Versions].

• Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review - 2018. [All Versions]. [Slides]. Sergey Levine's tutorial on treating reinforcement learning probabilisticly.

• Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability - NIPS'21, 2021. [All Versions]. A formal treatment on the generalization problem in reinforcement learning.

• On the Expressivity of Markov Reward - NIPS'21, 2021. [All Versions]. A formal treatment of tasks and rewards in reinforcement learning modeling.

• Constrained Policy Optimization - ICML'17, 2017. [All Versions]. The original paper on constrained reinforcement learning (safe reinforcement learning).

• The Quest for a Common Model of the Intelligent Decision Maker - Multi-disciplinary Conference on Reinforcement Learning and Decision Making'22, 2022. [All Versions]. Richard Sutton's perspective on the future directions of reinforcement learning research.

Problem Solving / Inverse Reinforcement Learning

• Apprenticeship Learning via Inverse Reinforcement Learning - ICML'04, 2004. [All Versions]. Pieter Abbeel and Andrew Ng's original paper on inverse reinforcement learning (IRL).

Learning with Cognitive Plausibility / Commonsense Knowledgebase

• Accuracy and Precision - Wikipedia. Wikipedia on the distinctions and the trade-off between accuracy and precision.

• Recognition-by-Components: A Theory of Human Image Understanding - Psychological Review, 1987. [All Versions]. The original paper on the recognition-by-components theory.

• Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense - Engineering, 2020. [All Versions]. Yixin Zhu and Song-Chun Zhu's review on visual commonsense.

• Self-supervised Learning Through the eyes of a Child - NIPS'20, 2020. [All Versions]. Concept learning through near-natural co-occurrence frequency estimation.

• BONGARD-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning - NIPS'20, 2020. [All Versions].

• Learning and development in networks: The importance of starting small. - Cognition, 1993. [All Versions]. The original paper on the idea of curriculum learning.

• Curriculum Learning - ICML'09, 2009. [All Versions]. The original paper applying the idea of curriculum learning to machine learning.

• Inferring "Dark Matter" and "Dark Energy" from Videos - ICCV'13, 2013. [All Versions]. The original paper on latent state discovery from videos.

Jul 21, 2022

Paper Reading

• It's not just you: science papers are getting harder to read - Nature, 2017. [All Versions]. Nature perspective on reading scientific papers.

Jul 20, 2022

Knowledge Management

• Communicating with Slip Boxes - 2019. [All Versions].

Jul 18, 2022

Knowledge Management

• The Zettelkasten Method - Bielefeld University. Relating ideas in graphs and multi-labels.

• Niklas Luhmann's Card Index: Thinking Tool, Communication Partner, Publication Machine - Forgetting Machines: Knowledge Management Evolution in Early Modern Europe, Brill, 2016. [All Versions].

Jul 16, 2022

Methodologies for Experiments / Virtual Reality

• Virtual reality: A survival guide for the social scientist - Journal of Media Psychology, 2009. [All Versions].

Stanford / Commonsense Knowledgebase

• Jeremy Bailenson - Department of Communication, Stanford, Virtual Human Interaction Lab (VHIL) - Stanford.

Jul 15, 2022

Abduction / Rationalization

• Rationalizing constraints on the capacity for cognitive control - Trends in Cognitive Sciences, 2021. [All Versions].

Jul 14, 2022

Communications / Pointing & Pantomime

• 12- and 18-Month-Olds Point to Provide Information for Others - Journal of Cognition and Development, 2009. [All Versions].

Jul 11, 2022

Commonsense / Commonsense Knowledgebase

• Open Mind Common Sense: Knowledge Acquisition from the General Public - OTM Confederated International Conferences'02, 2002. [All Versions].

Jul 09, 2022

Problem Solving / Planning

• Learning to act by integrating mental simulations and physical experiments - CogSci'21, 2018. [All Versions].

Commonsense / AI Commonsense Reasoning

• Human-like property induction is a challenge for large language models - CogSci'22, 2022.

Jul 08, 2022

Courses

• Introduction to Program Synthesis - MIT. Armando Solar-Lezama's elementary course on program synthesis.

UCLA / Commonsense Knowledgebase

• Song-Chun Zhu - Department of Statistics, Department of Computer Science, UCLA.

• Tao Gao - UCLA, Visual Intelligence Lab - Department of Statistics, Department of Psychology, UCLA.

• Hongjing Lu - UCLA, Computational Vision and Learning Lab (CVL) - Department of Psychology, Department of Statistics, UCLA.

Jul 07, 2022

Meta-Level Considerations / Marr's Levels of Analysis

• Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic - Topics in Cognitive Science, 2015. [All Versions].

Jul 06, 2022

Meta-Level Considerations / Marr's Levels of Analysis

• From understanding computation to understanding neural circuitry - Neuroscience Research Program Bulletin, 1979. [All Versions].

Jul 03, 2022

Inductive Logic & Program Synthesis / Commonsense Knowledgebase

• AutumnSynth: Synthesis of Reactive Programs with Structured Latent State - NIPS'21 AIPLANS Workshop, 2021. [All Versions].

Jul 02, 2022

Literature Management

• Goodbye, Microsoft Academic – Hello, open research infrastructure? - LSE Impact Blog, 2021. An interpretation of Microsoft's strategy on research infrastructure.

Jun 24, 2022

Inductive Logic & Program Synthesis / Commonsense Knowledgebase

• Program Synthesis with Large Language Models - 2021. [All Versions].

Jun 11, 2022

Knowledge Representation / Commonsense Knowledgebase

• Learning Program Representations for Food Images and Cooking Recipes - CVPR'22, 2022. [All Versions].

Jun 04, 2022

Commonsense / AI Commonsense Reasoning

• The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning - 2022. [All Versions].

May 28, 2022

Complexity & Information Theory / Visual Complexity

• Identifying concept libraries from language about object structure - CogSci'22, 2022. [All Versions].

May 27, 2022

Communications / Pragmatics

• When Lingens meets Frege: communication without common ground - Philosophical Studies, 2021. [All Versions].

May 17, 2022

Methodologies for Experiments / Quantitative Analysis

• Two lines: A valid alternative to the invalid testing of U-shaped relationships with quadratic regressions - Advances in Methods and Practices in Psychological Science, 2018. [All Versions]. An alternative method to test the statistical significance of U-shaped relationships.

May 14, 2022

Complexity & Information Theory / Theory

• Visual Pattern Discrimination - IRE Transactions on Information Theory, 1962. [All Versions].

May 12, 2022

John Hopcroft / Commonsense Knowledgebase

• Foundations of Data Science - Cambridge University Press. [All Versions].

May 10, 2022

Explainability / Explainable Deep Learning

• pytorch-grad-cam (⭐6.2k) - 2021. Class Activation Map methods implemented in Pytorch, with many elegant features.

May 09, 2022

Literature Management

• Microsoft Academic Graph - Microsoft Research. Heterogeneous graph containing scientific publication records, citation relationships between those publications, as well as authors, institutions, journals, conferences, and fields of study.

• An Overview of Microsoft Academic Service (MAS) and Applications - WWW'15, 2015. [All Versios]. Original paper on Microsoft Academic Graph.

• Semantic Scholar - Allen Institute for AI Research. AI-powered scientific literature research tool.

• VOSviewer - Leiden University. For constructing and visualizing bibliometric networks.

May 08, 2022

System 1 & System 2 / Dual-Coding Theory

• Rational arbitration between statistics and rules in human sequence processing - Nature Human Behavior, 2022. [All Versions].

May 02, 2022

System 1 & System 2 / Dual-Coding Theory

• Different computational relations in language are captured by distinct brain systems - Cerebral Cortex, 2022. [All Versions].

Apr 30, 2022

Complexity & Information Theory / Theory

• A Mathematical Theory of Communication - The Bell System Technical Journal, 1948. [All Versions]. Shannon's original paper on Information Theory.

Apr 29, 2022

Analogy / Scientific Writing

• Skip-Gram − Zipf + Uniform = Vector Additivity - ACL'17, 2017. [All Versions].

Apr 28, 2022

Bayesian Modeling / Bayesian Induction

• The rational basis of representativeness - CogSci'01, 2001. [All Versions].

• Testing a Bayesian Measure of Representativeness Using a Large Image Database - NIPS'11, 2011. [All Versions].

• Constructing a hypothesis space from the Web for large-scale Bayesian word learning - CogSci'12, 2012. [All Versions].

Apr 27, 2022

Bayesian Modeling / Generative Model

• Score-Based Generative Modeling through Stochastic Differential Equations - ICLR'21, 2021. [All Versions].

Apr 26, 2022

Complexity & Information Theory / Theory

• From Algorithmic to Subjective Randomness - NIPS'03, 2003. [All Versions].

Apr 21, 2022

Explainability / Strong Machine Learning

• Deep Forest: Towards An Alternative to Deep Neural Networks - IJCAI'17, 2017. [All Versions]. [Project (⭐791)].

Apr 20, 2022

Explainability / Trustworthy AI

• CoCoX: Generating Conceptual and Counterfactual Explanations via Fault-Lines - AAAI'20, 2020. [All Versions].

Explainability / Strong Machine Learning

• Beneficial and harmful explanatory machine learning - Machine Learning, 2021. [All Versions].

Apr 16, 2022

Bayesian Modeling / Generative Model

• Cooperative Training of Descriptor and Generator Networks - IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. [All Versions].

Apr 14, 2022

Complexity & Information Theory / Visual Complexity

• Image complexity and spatial information - International Workshop on Quality of Multimedia Experience, 2013. [All Versions].

Explainability / Explainable Deep Learning

• Individual differences among deep neural network models - Nature Communications, 2020. [All Versions].

Apr 13, 2022

Methodologies for Experiments / Scaling Up Behavioral Studies

• Exploring human cognition using large image databases - Topics in Cognitive Sciences, 2016. [All Versions].

Methodologies for Experiments / Human-Machine Comparison

• Humans can decipher adversarial images - Nature Communications. 2019. [All Versions].

Apr 12, 2022

Problem Solving / Reinforcement Learning

• A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation - NIPS'19, 2019. [All Versions].

Apr 11, 2022

Bayesian Modeling / Generative Model

• Latent Space Factorisation and Manipulation via Matrix Subspace Projection - ICML'20, 2020. [All Versions].

Meta-Level Considerations / Meta Learning

• Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables - ICML'19, 2019. [All Versions].

• Balancing Constraints and Rewards with Meta-Gradient D4PG - ICLR'21, 2021. [All Versions].

• Metacontrol for Adaptive Imagination-Based Optimization - ICLR'17, 2017. [All Versions].

• On Effective Scheduling of Model-based Reinforcement Learning - NIPS'21, 2021. [All Versions].

Apr 08, 2022

Methodologies for Experiments / Scaling Up Behavioral Studies

• Machine-generated theories of human decision-making - Science, 2021. [All Versions].

• Integrating explanation and prediction in computational social science - Nature, 2021. [All Versions].

Methodologies for Experiments / Question Answering

• Do People Ask Good Questions? - Computational Brain & Behavior, 2018. [All Versions].

• Asking goal-oriented questions and learning from answers - CogSci'19, 2019. [All Versions].

Apr 04, 2022

System 1 & System 2 / Dual-Coding Theory

• A continuous semantic space describes the representation of thousands of object and action categories across the human brain - Neuron, 2012. [All Versions].

Learning with Cognitive Plausibility / Commonsense Knowledgebase

• Interplay between rule learning and rule switching in a perceptual categorization task - 2022. [All Versions].

Apr 01, 2022

Problem Solving / Reinforcement Learning

• Automatic curriculum learning for deep RL: a short survey - IJCAI'20, 2020. [All Versions].

• TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL - ICML'21, 2021. [All Versions]. [Project (⭐52)].

Mar 28, 2022

Problem Solving / Reinforcement Learning

• SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning - ICML'21, 2021. [All Versions].

Mar 24, 2022

Courses

• Computational Cognitive Science Courses - MIT, Harvard, Stanford. Courses on computational cognitive science from MIT, Harvard, Stanford.

Programming

• Probabilistic Models of Cognition - MIT. The probabilistic approach to cognitive science, which models learning and reasoning as inference in complex probabilistic models.

Paper Writing

• How to construct a Nature summary paragraph - Nature. Nature official guidelines for composing abstracts.

• The Machine Learning Reproducibility Checklist - McGill University. Guidelines for introducing a machine learning algorithm with guarantee of reproducibility.

Communications / Pragmatics

• Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding - Transactions of the Association for Computational Linguistics, 2017. [All Versions].

• Pragmatically Informative Image Captioning with Character-Level Inference - NAACL'18, 2018. [All Versions].

Mar 22, 2022

Commonsense / AI Commonsense Reasoning

• Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning - EMNLP'21, 2021. [All Versions].

Mar 21, 2022

System 1 & System 2 / Dual-Coding Theory

• The Deese-Roediger-McDermott (DRM) task: A simple cognitive paradigm to investigate false memories in the laboratory - Journal of Visualized Experiments, 2017. [All Versions].

Mar 18, 2022

Bayesian Modeling / Generative Model

• Unsupervised Representaton Learning with Deep Convolutional Generative Adversarial Networks - ICLR'16, 2016. [All Versions].

Mar 17, 2022

Learning with Cognitive Plausibility / Commonsense Knowledgebase

• Graininess of judgment under uncertainty: An accuracy-informativeness trade-off - Journal of Experimental Psychology, 1995. [All Versions].

• Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms - ICLR'20, 2020. [All Versions].

UC Berkeley / Commonsense Knowledgebase

• Anca Dragan - EECS, Berkeley, Interactive Autonomy and Collaborative Technologies Laboratory (InterACT) - Berkeley.

Mar 16, 2022

Paper Writing

• Scientific Papers - Nature. Nature guidance on writing scientific papers.

Paper Reading

• How to (seriously) read a scientific paper - Science, 2016. [All Versions]. Science interview on reading scientific papers.

• How to navigate a scientific paper with time constraints: a graphics approach - MIT. MIT guidance on strategies for reading papers given different time constraints.

Literature Management

• How to keep up with the scientific literature - Science, 2016. Science interview on organizing scientific papers.

• Scientific literature: Information overload - Nature, 2016. [All Versions]. Perspective on handling overloaded information from scientific literature.

Mar 15, 2022

Problem Solving / Intrinsic Motivation

• What is intrinsic motivation? A typology of computational approaches - Frontiers in Neurorobotics, 2009. [All Versions].

• Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning - ICML'21, 2021. [All Versions].

Mar 14, 2022

Methodologies for Experiments / Human-Machine Comparison

• Shared computational principles for language processing in humans and deep language models - Nature Neuroscience, 2022. [All Versions].

Mar 11, 2022

Communications / Pragmatics

• Pragmatic Reasoning through Semantic Inference - Semantics & Pragmatics, 2016. [All Versions].

Mar 05, 2022

Commonsense / Commonsense Knowledgebase

• Verbosity: A Game for Collecting Common-Sense Facts - CHI'06, 2006. [All Versions].

• Designing games with a purpose - Communications of the ACM, 2008. [All Versions].

• Acquiring Comparative Commonsense Knowledge from the Web - AAAI'14, 2014. [All Versions].

Mar 04, 2022

System 1 & System 2 / Dual-Coding Theory

• Organizational Principles of Abstract Words in the Human Brain - Cerebral Cortex, 2018. [All Versions].

System 1 & System 2 / Neural-Symbolic AI

• Combining Logical Abduction and Statistical Induction: Discovering Written Primitives with Human Knowledge - AAAI'17, 2017. [All Versions].

Mar 03, 2022

Cognitive Development / Commonsense Knowledgebase

• Perception of partly occluded objects in infancy - Cognitive Psychology, 1983. [All Versions].

Feb 27, 2022

Learning with Cognitive Plausibility / Commonsense Knowledgebase

• Attention over Learned Object Embeddings Enables Complex Visual Reasoning - NIPS'21, 2021. [All Versions].

Feb 24, 2022

Cognitive Development / Commonsense Knowledgebase

• Observing the unexpected enhances infants' learning and exploration - Science, 2015. [All Versions].

Feb 23, 2022

Causality / Scientific Writing

• Do six-month-old infants perceive causality? - Cognition, 1987. [All Versions].

Feb 21, 2022

System 1 & System 2 / Neural-Symbolic AI

• Grounded Language Learning Fast and Slow - ICLR'21, 2021. [All Versions]. [Project (⭐46)].

Feb 20, 2022

Problem Solving / Reinforcement Learning

• Learning to Perform Physics Experiments via Deep Reinforcement Learning - ICLR'17, 2017. [All Versions].

Feb 18, 2022

Learning in the Open World / Commonsense Knowledgebase

• Ontology-guided Semantic Composition for Zero-Shot Learning - KR'20, 2020. [All Versions].

• OntoZSL: Ontology-enhanced Zero-shot Learning - WWW'21, 2021. [All Versions].

• Knowledge-aware Zero-Shot Learning: Survey and Perspective - IJCAI'21 2021. [All Versions].

• From Red Wine to Red Tomato: Composition with Context - CVPR'17, 2017. [All Versions].

• Attributes as Operators: Factorizing Unseen Attribute-Object Compositions - ECCV'18, 2018. [All Versions].

• Learning Compositional Representations for Few-Shot Recognition - CVPR'19, 2019. [All Versions].

• Symmetry and Group in Attribute-Object Compositions - CVPR'20, 2020. [All Versions].

• A causal view of compositional zero-shot recognition - NIPS'20, 2020. [All Versions].

• Compositional Few-Shot Recognition with Primitive Discovery and Enhancing - MM'20, 2020. [All Versions].

• Learning Unseen Concepts via Hierarchical Decomposition and Composition - CVPR'20, 2020. [All Versions].

Feb 16, 2022

Knowledge Representation / Commonsense Knowledgebase

• Qualitative and quantitative simulation: bridging the gap - Artificial Intelligence, 1997. [All Versions].

Feb 15, 2022

NYU / Commonsense Knowledgebase

• Gary Marcus - Department of Psychology, NYU.

Feb 14, 2022

NYU / Commonsense Knowledgebase

• Ernest Davis - Department of Computer Science, Courant Institute of Mathematical Sciences, NYU.

Feb 12, 2022

Bayesian Modeling / Generative Model

• A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs - Science, 2017. [All Versions].

Feb 11, 2022

Abduction / Applications in AI

• Probabilistic Sufficient Explanations - IJCAI'21, 2021. [All Versions].

Feb 08, 2022

Theory of Mind / Scientific Writing

• PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception - AAAI'21, 2021. [All Versions]. [Project].

Feb 07, 2022

Causality / Scientific Writing

• Eye-tracking causality - Psychological Science, 2017. [All Versions].

Feb 06, 2022

Theory of Mind / Scientific Writing

• Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration - ICLR'21, 2021. [All Versions].

Feb 04, 2022

System 1 & System 2 / Neural-Symbolic AI

• Hybrid computing using a neural network with dynamic external memory - Nature, 2016. [All Versions].

Jan 30, 2022

Bayesian Modeling / Generative Model

• Learning Energy-Based Models by Diffusion Recovery Likelihood - ICLR'21, 2021. [All Versions]. [Code (⭐40)].

Jan 29, 2022

Commonsense / Intuitive Physics

• Learning physical parameters from dynamic scenes - Cognitive Psychology, 2017. [All Versions].

• Partial Mental Simulation Explains Fallacies in Physical Reasoning - 2021. [All Versions].

Jan 28, 2022

Problem Solving / Human-Level Problem Solving

• Abstract strategy learning underlies flexible transfer in physical problem solving - CogSci'20, 2020. [All Versions].

• Physion: Evaluating Physical Prediction from Vision in Humans and Machines - NIPS'21, 2021. [All Versions].

Jan 22, 2022

MIT / Commonsense Knowledgebase

• Josh Tenenbaum - MIT, Computational Cognitive Science Group (CoCoSci Group) - Department of Brain and Cognitive Sciences, CSAIL, MIT.

• Leslie Kaelbling - MIT, The Learning & Intelligent Systems Group - Department of Electrical Engineering and Computer Science, CSAIL, MIT.

• Armando Solar-Lezama - MIT, Computer-Aided Programming Group - Department of Electrical Engineering and Computer Science, CSAIL, MIT.

Jan 21, 2022

UCLA / Commonsense Knowledgebase

• Ying Nian Wu - Department of Statistics, UCLA.

• Guy Van den Broeck - UCLA, StarAI Lab - Department of Computer Science, UCLA.

Jan 14, 2022

Bayesian Modeling / Generative Model

• Parameter Expansion for Data Augmentation - Journal of the American Statistical Association, 1999. [All Versions].

Jan 09, 2022

Bayesian Modeling / Generative Model

• Minimax entropy principle and its application to texture modeling - Neural Computing, 1997. [All Versions].

Jan 08, 2022

Problem Solving / Inverse Reinforcement Learning

• Inverse Constrained Reinforcement Learning - ICML'21, 2021. [All Versions].

Jan 04, 2022

Bayesian Modeling / Generative Model

• Efficient Learning of Sparse Representations with an Energy-Based Model - NIPS'06, 2006. [All Versions].

Meta-Level Considerations / Gestalt

• Thoughts beyond words: When language overshadows insight - Journal of Experimental Psychology, 1993. [All Versions].

Jan 01, 2022

Bayesian Modeling / Bayesian Optimization

• Taking the Human Out of the Loop: A Review of Bayesian Optimization - Proceedings of the IEEE, 2015. [All Versions].

Dec 31, 2021

Cognitive Development / Commonsense Knowledgebase

• Word, thought, and deed: the role of object categories in children's inductive inferences and exploratory play - Developmental Psychology, 2009. [All Versions].

Dec 30, 2021

Knowledge Representation / Commonsense Knowledgebase

• Commonsense reasoning about causality: Deriving behavior from structure - Artificial Intelligence, 1984. [All Versions].

Dec 27, 2021

Bayesian Modeling / Nonparametric Model

• Nonparametric Bayesian Data Analysis - Statistical Science, 2004. [All Versions].

Dec 26, 2021

Bayesian Modeling / Nonparametric Model

• Infinite Hidden Relational Models - UAI'06, 2006. [All Versions].

Dec 23, 2021

Meta-Level Considerations / Gestalt

• Restructuring revisited II. An information processing theory of restructuring and insight - Scandinavian Journal of Psychology, 1984. [All Versions].

Dec 19, 2021

Stanford / Commonsense Knowledgebase

• Michael Frank - Stanford, The Stanford Language and Cognition Lab - Department of Psychology, Stanford.

Dec 12, 2021

Communications / Pragmatics

• Language as shaped by the environment: linguistic construal in a collaborative spatial task - Nature Humanities and Social Sciences Communications, 2020. [All Versions].

Dec 11, 2021

Problem Solving / Reinforcement Learning

• A Survey of Preference-Based Reinforcement Learning Methods - Journal of Machine Learning Research, 2017. [All Versions].

Nov 29, 2021

Harvard / Commonsense Knowledgebase

• Elizabeth Spelke - Harvard, Harvard Laboratory for Developmental Studies - Department of Psychology, Harvard.

Nov 28, 2021

Harvard / Commonsense Knowledgebase

• Samuel Gershman - Harvard, Computational Cognitive Neuroscience Lab (CCN Lab) - Department of Psychology, Harvard.

Nov 27, 2021

Harvard / Commonsense Knowledgebase

• Tomer Ullman - Harvard, Computation, Cognition, and Development Lab (CoCoDev) - Department of Psychology, Harvard.

Nov 24, 2021

Problem Solving / Inverse Reinforcement Learning

• Generalized Inverse Planning: Learning Lifted non-Markovian Utility for Generalizable Task Representation - 2020. [All Versions].

Nov 22, 2021

UCLA / Commonsense Knowledgebase

• Center for Vision, Cognition, Learning and Autonomy (VCLA) - Department of Statistics, UCLA.

Nov 21, 2021

Karl Popper / Commonsense Knowledgebase

• The logic of scientific discovery - Routledge, 2005. [All Versions].

Nov 19, 2021

Meta-Level Considerations / Gestalt

• Restructuring revisited I. Summary and critique of the Gestalt theory of problem solving - Scandinavian Journal of Psychology, 1984. [All Versions].

Karl Popper / Commonsense Knowledgebase

• All Life is Problem Solving - Routledge, 2001. [All Versions].

Nov 18, 2021

Abduction / Explanation

• Abductive Cognition: The Epistemological and Eco-Cognitive Dimensions of Hypothetical Reasoning - Springer, 2009. [All Versions].

• The Role of Explanatory Considerations in Updating - Cognition, 2015. [All Versions].

• Use of current explanations in multicausal abductive reasoning - Cognitive Science, 2001. [All Versions].

• Kinematic mental simulations in abduction and deduction - Proceedings of National Academy of Sciences, 2013. [All Versions].

• Abduction: A categorical characterization - Journal of Applied Logic, 2015. [All Versions].

• Defending Abduction - Philosophy of Science, 1999. [All Versions].

• Abduction − the context of discovery + underdetermination = inference to the best explanation - Synthese, 2019. [All Versions].

• Towards an Architecture for Cognitive Vision Using Qualitative Spatio-temporal Representations and Abduction - Spatial Cognition, 2002. [All Versions].

• Abductive inference within a pragmatic framework - Synthese, 2018. [All Versions].

• Disjunctive Abduction - New Generation Computing, 2019. [All Versions].

• The order effect in human abductive reasoning: an empirical and computational study - Journal of Experimental & Theoretical Artificial Intelligence, 2006. [All Versions].

• The AHA! Experience: Creativity Through Emergent Binding in Neural Networks - Cognitive Science, 2012. [All Versions].

Abduction / Scientific Discovery

• Exploring science: The cognition and development of discovery processes - MIT Press, 2000. [All Versions].

• Hypothesis generation, sparse categories, and the positive test strategy - Psychological Review, 2011. [All Versions].

Abduction / Applications in AI

• Abductive Inference in Bayesian Networks: A Review - Advances in Bayesian Networks, 2004. [All Versions].

• Bayesian Abductive Logic Programs: A Probabilistic Logic for Abductive Reasoning - IJCAI'11, 2011. [All Versions].

• Abductive Plan Recognition by Extending Bayesian Logic Programs - ECML'11, 2011. [All Versions].

• An Approach to Abductive Reasoning in Equational Logic - IJCAI'13, 2013. [All Versions].

• Abduction-Based Explanations for Machine Learning Models - AAAI'19, 2019. [All Versions].

• Discovering a symbolic planning language from continuous experience - CogSci'19, 2019. [All Versions].

Bayesian Modeling / Nonparametric Model

• Learning Systems of Concepts with an Infinite Relational Model - AAAI'06, 2006. [All Versions].

• The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies - Journal of the ACM, 2010. [All Versions].

Susan Carey / Commonsense Knowledgebase

• Conceptual Change in Childhood - MIT Press, 1985. [All Versions].

• The Origin of Concepts - Oxford University Press, 2009. [All Versions].

Communications / Visual Communication

• The Picture Exchange Communication System - Behavior Modification, 1994. [All Versions].

• A multimodal discourse theory of visual narrative - Journal of Pragmatics, 2014. [All Versions].

Communications / Pragmatics

• How young children integrate information sources to infer the meaning of words - Nature, 2021. [All Versions].

• Information Structure in Discourse: Towards an Integrated Formal Theory of Pragmatics - Semantics and Pragmatics, 1998. [All Versions].

Communications / Language Compositionality

• Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols - NIPS'18, 2018. [All Versions].

• Emergent communication through negotiation - ICLR'18, 2018. [All Versions].

• The language of generalization - Psychological Review, 2019. [All Versions].

• Compositionality and Generalization in Emergent Languages - ACL'20, 2020. [All Versions].

Problem Solving / Human-Level Problem Solving

• Learning to Solve Problems: A Handbook for Designing Problem-Solving Learning Environments - Taylorfrancis, 2010. [All Versions].

• Human Performance on Insight Problem Solving: A Review - The Journal of Problem Solving, 2011. [All Versions].

• Learning to perceive and act by trial and error - Machine Learning, 1991. [All Versions].

• Representations in distributed cognitive tasks - Cognitive Science, 1994. [All Versions].

• The nature of external representations in problem solving - Cognitive Science, 1997. [All Versions].

• Exploration: from machines to humans - Current Opinion in Behavioral Sciences, 2020. [All Versions].

• Balancing exploration and exploitation with information and randomization - Current Opinion in Behavioral Sciences, 2021. [All Versions].

• Hippocampal neurons construct a map of an abstract value space - Cell, 2021. [All Versions].

Problem Solving / Planning

• What Is the Model in Model-Based Planning? - Cognitive Science, 2021. [All Versions].

Problem Solving / Reinforcement Learning

• Solving Compositional Reinforcement Learning Problems via Task Reduction - ICLR'21, 2021. [All Versions].

• Neural Task Programming: Learning to Generalize Across Hierarchical Tasks - ICRA'18, 2018. [All Versions].

• Learning to act: qualitative learning of deterministic action models - Journal of Logic and Computation, 2017. [All Versions].

• Learning to Act and Observe in Partially Observable Domains - 2021. [All Versions].

• Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation - Robotics and Automation Letters, 2021. [All Versions].

Problem Solving / Inverse Reinforcement Learning

• From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following - ICLR'19, 2019. [All Versions].

• Few-shot Bayesian imitation learning with logical program policies. - AAAI'20, 2020. [All Versions].

System 1 & System 2 / Neural-Symbolic AI

• Neural Logic Reinforcement Learning - ICML'19, 2019. [All Versions].

• Abductive learning: towards bridging machine learning and logical reasoning - Science China Information Sciences, 2019. [All Versions].

• Abductive Knowledge Induction From Raw Data - IJCAI'21, 2021. [All Versions].

• Making sense of sensory input - Artificial Intelligence, 2021. [All Versions].

• Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Execution - CVPR'21, 2021. [All Versions].

• Learn to explain efficiently via neural logic inductive learning - ICLR'20, 2020. [All Versions]. [Project (⭐34)].

• Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning - ICML'20, 2020. [All Versions].

• Generating new concepts with hybrid neuro-symbolic models. - CogSci'20, 2020. [All Versions].

• Learning Task-General Representations with Generative Neuro-Symbolic Modeling - ICLR'21, 2021. [All Versions].

• Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components - NIPS'19, 2019. [All Versions].

• Neuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning” - ICML'20, 2020. [All Versions].

• Understanding Deep Architectures with Reasoning Layer - NIPS'20, 2020. [All Versions].

• An Explicitly Relational Neural Network Architecture - ICML'20, 2020. [All Versions].

• Compositional Generalization via Neural-Symbolic Stack Machines - NIPS'20, 2020. [All Versions].

• Stochastic Optimization of Sorting Networks via Continuous Relaxations - ICLR'19, 2019. [All Versions].

• Program Guided Agent - ICLR'20, 2020. [All Versions].

• Learning Compositional Rules via Neural Program Synthesis - NIPS'20, 2020. [All Versions].

• Discovering Symbolic Models from Deep Learning with Inductive Biases - NIPS'20, 2020. [All Versions].

• Neural Logic Machines - ICLR'19, 2019. [All Versions].

• The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision - ICLR'19, 2019. [All Versions].

• Visual Concept-Metaconcept Learning - NIPS'19, 2019. [All Versions].

• Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning - ICLR'21, 2021. [All Versions].

• Temporal and Object Quantification Networks - IJCAI'21, 2021. [All Versions].

Explainability / Explainable Deep Learning

• This Looks Like That: Deep Learning for Interpretable Image Recognition - NIPS'19, 2019. [All Versions].

• Unsupervised learning by competing hidden units - Proceedings of National Academy of Sciences, 2019. [All Versions].

Embodied Intelligence / Explainable Deep Learning

• Rapid Assimilation of External Objects Into the Body Schema - Psychological Science, 2010. [All Versions].

• The cognitive bases of human tool use - Behavioral and Brain Sciences, 2012. [All Versions].

• The embodied mind extended: using words as social tools - Frontiers in Psychology, 2013. [All Versions].

• Tool use as adaptation - Philosophical Transactions of the Royal Society B: Biological Sciences, 2013. [All Versions].

• Intensive tool-practice and skillfulness facilitate the extension of body representations in humans - Neuropsychologia, 2014. [All Versions].

• Meta-strategy learning in physical problem-solving: the effect of embodied experience - CogSci'21, 2021. [All Versions].

• Robotic hand augmentation drives changes in neural body representation - Science Robotics, 2021. [All Versions].

• Expert Tool Users Show Increased Differentiation between Visual Representations of Hands and Tools - Journal of Neuroscience, 2021. [All Versions].

• Visual scoping operations for physical assembly - CogSci'21, 2021. [All Versions].

• Behavior-grounded representation of tool affordances - ICRA'05, 2005. [All Versions].

• A Relational Approach to Tool-Use Learning in Robots - ILP'12, 2012. [All Versions].

• Relational affordances for multiple-object manipulation - Autonomous Robots, 2017. [All Versions].

• Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight - RSS'19, 2019. [All Versions].

• Meta-strategy learning in physical problem-solving: the effect of embodied experience - 2021. [All Versions].

Methodologies for Experiments / Human-Machine Comparison

• Problem Solving and Rule Induction: A Unified View - Knowledge and cognition, 1974. [All Versions].

• Evidence integration in model-based tree search - Proceedings of National Academy of Sciences, 2015. [All Versions].

• People Infer Recursive Visual Concepts from Just a Few Examples - Computational Brain & Behavior, 2020. [All Versions].

• One-shot learning of generative speech concepts - CogSci'14, 2014. [All Versions].

• Human few-shot learning of compositional instructions - CogSci'19, 2019. [All Versions].

• Fast and flexible: Human program induction in abstract reasoning tasks - CogSci'21, 2021. [All Versions].

• Investigating Human Priors for Playing Video Games - ICML'18, 2018. [All Versions].

• Tasks for aligning human and machine planning - Current Opinion in Behavioral Sciences, 2019. [All Versions].

Meta-Level Considerations / Cognitive Architecture

• SOAR: An architecture for general intelligence - Artificial Intelligence, 1987. [All Versions].

• Metacognition in computation: A selected research review - Artificial Intelligence, 2005. [All Versions].

• Basic functional trade-offs in cognition: An integrative framework - Cognition, 2018. [All Versions].

• A Theoretical Computer Science Perspective on Consciousness - Journal of Artificial Intelligence and Consciousness, 2020. [All Versions].

Theory of Mind / Scientific Writing

• The Signature of All Things: Children Infer Knowledge States from Static Images - CogSci'20, 2020. [All Versions].

• Rational quantitative attribution of beliefs, desires and percepts in human mentalizing - Nature Human Behavior, 2017. [All Versions].

• The Bayesian Brain: An Introduction to Predictive Processing - 2018.

• Machine theory of mind - ICML'18, 2018. [All Versions].

• Theory of mind as inverse reinforcement learning - Current Opinion in Behavioral Sciences, 2019. [All Versions].

• Computational Models of Emotion Inference in Theory of Mind: A Review and Roadmap - Topics in Cognitive Science, 2019. [All Versions].

• The Naïve Utility Calculus as a unified, quantitative framework for action understanding - Cognitive Psychology, 2021. [All Versions]. [Project].

• Leveraging Facial Expressions and Contextual Information to Investigate Opaque Representations of Emotion - Emotion, 2019. [All Versions].

• Waiting and weighting: Information sampling is a balance between efficiency and error-reduction - Cognition, 2013. [All Versions].

• Natural scene statistics account for the representation of scene categories in human visual cortex - Neuron, 2013. [All Versions].

• Unit of visual working memory: A Boolean map provides a better account than an object does - Journal of Experimental Psychology, 2020. [All Versions].

• The logic of universalization guides moral judgment - Proceedings of National Academy of Sciences, 2020. [All Versions].

• Origins of the concepts cause, cost, and goal in prereaching infants - Proceedings of National Academy of Sciences, 2019. [All Versions].

Analogy / Scientific Writing

• Generalize and Blend: Concept Blending Based on Generalization, Analogy, and Amalgams - ICCC'15, 2015. [All Versions].

• VISALOGY: Answering Visual Analogy Questions - NIPS'15, 2015. [All Versions].

• Detecting Unseen Visual Relations Using Analogies - CVPR'19, 2019. [All Versions].

• Learning to Make Analogies by Contrasting Abstract Relational Structure - ICLR'19, 2019. [All Versions].

• Sky + Fire = Sunset. Exploring Parallels between Visually Grounded Metaphors and Image Classifiers - ACL'20, 2020. [All Versions].

• Analogy as Nonparametric Bayesian Inference over Relational Systems - CogSci'20, 2020. [All Versions].

Causality / Scientific Writing

• Causal Reasoning - The Oxford Handbook of Cognitive Psychology, 2013. [All Versions].

• Inferring causal networks from observations and interventions - Cognitive Science, 2010. [All Versions].

• A Language for Counterfactual Generative Models - ICML'21, 2021. [All Versions].

• Constraints on Hypothesis Selection in Causal Learning - CogSci'15, 2015. [All Versions].

• What happened? Reconstructing the past through vision and sound - 2021. [All Versions].

• How do people generalize causal relations over objects? A non-parametric Bayesian account - 2021. [All Versions].

Commonsense / AI Commonsense Reasoning

• From Recognition to Cognition: Visual Commonsense Reasoning - CVPR'19, 2019. [All Versions]. [Project].

• PIQA: Reasoning about Physical Commonsense in Natural Language - AAAI'20, 2020. [All Versions].

• Visual Commonsense R-CNN - CVPR'20, 2020. [All Versions].

• VisualCOMET: Reasoning About the Dynamic Context of a Still Image - ECCV'20, 2020. [All Versions].

Inductive Logic & Program Synthesis / Commonsense Knowledgebase

• Towards combining inductive logic programming with Bayesian networks - ILP'01, 2001. [All Versions].

• Learning Efficient Logical Robot Strategies Involving Composable Objects - IJCAI'15, 2015. [All Versions].

• Learning Higher-Order Logic Programs through Abstraction and Invention - IJCAI'16, 2016. [All Versions].

• How Much Can Experimental Cost Be Reduced in Active Learning of Agent Strategies? - ILP'18, 2018. [All Versions].

• Meta-Interpretive Learning from noisy images - Machine Learning, 2018. [All Versions].

• Learning efficient logic programs - Machine Learning, 2018. [All Versions].

• Learning higher-order logic programs - Machine Learning, 2019. [All Versions].

• Logical reduction of metarules - Machine Learning, 2019. [All Versions].

• Playgol: Learning Programs Through Play - IJCAI'19, 2019. [All Versions].

• Machine Discovery of Comprehensible Strategies for Simple Games Using Meta-interpretive Learning - New Generation Computing, 2019. [All Versions].

• Forgetting to Learn Logic Programs - AAAI'20, 2020. [All Versions].

• Turning 30: New Ideas in Inductive Logic Programming - IJCAI'20, 2020. [All Versions].

• Learning programs by learning from failures - Machine Learning, 2020. [All Versions].

• Complete Bottom-Up Predicate Invention in Meta-Interpretive Learning - IJCAI'20, 2020. [All Versions].

• Meta-Interpretive Learning as Metarule Specialisation - Machine Learning, 2021. [All Versions].

• Derivative-free optimization of high-dimensional non-convex functions by sequential random embeddings - IJCAI'16, 2016. [All Versions].

• Finitely Generated Groups and First-Order Logic - Journal of The London Mathematical Society-second Series, 2005. [All Versions].

• Leveraging Language for Abstraction and Program Search - ICML'20, 2020. [All Versions].

• Program Synthesis Guided Reinforcement Learning - 2021. [All Versions].

• Learning Part-Based Abstractions for Visual Object Concepts - CogSci'21, 2021. [All Versions].

Knowledge Representation / Commonsense Knowledgebase

• The Analysis of Knowledge - Plato Stanford.

• Common Knowledge - Plato Stanford.

• Sense-Data - Plato Stanford.

• Epistemic Modal Logic - Wikipedia.

• Logics for Epistemic Programs - Synthese, 2004. [All Versions].

• A Translation Approach to Portable Ontology Specifications - Knowledge Acquisition, 1993. [All Versions].

• The Symbolic Grounding Problem - Physica D: Nonlinear Phenomena, 1990. [All Versions].

• Learning overhypotheses with hierarchical Bayesian models - Developmental Science, 2007. [All Versions].

• Learning Causal Schemata - CogSci'07, 2007, [All Versions].

• A Rational Analysis of Rule-Based Concept Learning - Cognitive Science, 2008. [All Versions].

• Modeling semantic cognition as logical dimensionality reduction - CogSci'08, 2008. [All Versions].

• Theory Acquisition as Stochastic Search - CogSci'10, 2010. [All Versions].

• A probabilistic model of theory formation - Cognition, 2010. [All Versions].

• Bootstrapping in a language of thought: A formal model of numerical concept learning - Cognition, 2012. [All Versions].

• Exploring the Conceptual Universe - Psychological Review, 2012. [All Versions].

• A taxonomy of inductive problems - Psychonomic Bulletin & Review, 2014. [All Versions].

• The Logical Primitives of Thought: Empirical Foundations for Compositional Cognitive Models - Psychological Review, 2016. [All Versions].

• The Emergence of Organizing Structure in Conceptual Representation - Cognitive Science, 2018. [All Versions].

• Theory Acquisition as Constraint-Based Program Synthesis - CogSci'21, 2021. [All Versions].

• Connecting perceptual and procedural abstractions in physical construction - CogSci'21, 2021. [All Versions].

• Invariant representation of physical stability in the human brain - 2021. [All Versions].

• Introduction to The Fluent Calculus - Linkoeping University Electronic Press, 1998. [All Versions].

• From situation calculus to fluent calculus: State update axioms as a solution to the inferential frame problem - Artificial Intelligence, 1999. [All Versions].

• Unsupervised Structure Learning of Stochastic And-Or Grammars - NIPS'13, 2013. [All Versions].

• Algorithms of Adaptation in Inductive Inference - 2021. [All Versions].

• A representational analysis of numeration systems - Cognition, 1995. [All Versions].

Cognitive Development / Commonsense Knowledgebase

• Cognitive development: An information processing approach - B.Blackwell, 1991. [All Versions].

• From exploration to play: A cross-sectional study of infant free play behavior - Developmental Psychology, 1981. [All Versions].

• Detecting Blickets: How Young Children Use Information about Novel Causal Powers in Categorization and Induction - Children Development, 2003. [All Versions].

• Serious fun: Preschoolers engage in more exploratory play when evidence is confounded - Developmental Psychology, 2007. [All Versions].

• Where science starts: Spontaneous experiments in preschoolers' exploratory play - Cognition, 2011. [All Versions].

• Scientific thinking in young children: Theoretical advances, empirical research, and policy implications - Science, 2012. [All Versions].

• Finding New Facts; Thinking New Thoughts - Advances in Child Development and Behavior, 2012. [All Versions].

• Theory learning as stochastic search in the language of thought - Cognitive Development, 2012. [All Versions].

• Infants make more attempts to achieve a goal when they see adults persist - Science, 2017. [All Versions].

• Knowing when to quit: Children consider access to solutions when deciding whether to persist - CogSci'20, 2020. [All Versions].

• Bayesian Models of Conceptual Development: Learning as Building Models of the World - Annual Review of Developmental Psychology, 2020. [All Versions].

• Sticking to the Evidence? A Behavioral and Computational Case Study of Micro-Theory Change in the Domain of Magnetism - Cognitive Science, 2019. [All Versions].

• Cognitive pragmatism: Children flexibly choose between facts and conjectures - CogSci'18, 2018. [All Versions].

• Exploratory play, rational action, and efficient search - CogSci'20, 2020. [All Versions].

• Children selectively endorse speculative conjectures - Child Development, 2021. [All Versions].

• Learning higher-order generalizations through free play: Evidence from 2- and 3-year-old children - Developmental Psychology, 2017. [All Versions].

• The Child as Hacker - Trends in Cognitive Sciences, 2020. [All Versions].

• Childhood as a solution to explore–exploit tensions - Philosophical Transactions of the Royal Society B: Biological Sciences, 2020. [All Versions].

• Children's exploratory play tracks the discriminability of hypotheses - Nature Communications, 2021. [All Versions].

• A Developmental Perspective on Executive Function - Child Development, 2010. [All Versions].

• Rethinking Executive Function and Its Development - Psychological Science, 2020. [All Versions].

Learning in the Open World / Commonsense Knowledgebase

• Online learning of symbolic concepts - Journal of Mathematical Psychology, 2017. [All Versions].

• Towards Open Set Deep Networks - CVPR'16, 2016. [All Versions].

• Adversarial Filters of Dataset Biases - ICML'20, 2020. [All Versions].

• A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning - 2020. [All Versions].

• Energy-Based Models for Continual Learning - NIPS'20, 2020. [All Versions]. [Project].

• Learning to Learn Image Classifiers with Visual Analogy - CVPR'18, 2018. [All Versions].

• Zero-Shot Object Detection - ECCV'18, 2018. [All Versions].

• Towards Open World Object Detection - CVPR'21, 2021. [All Versions]. [Project (⭐883)].

• Learning to Recognise Unseen Classes by A Few Similes - MM'17, 2017. [All Versions].

Learning with Cognitive Plausibility / Commonsense Knowledgebase

• Cognitive Science: Definition, Status, and Questions - Annual Review of Psychology, 1989. [All Versions].

• Machine Behaviour - Nature, 2019. [All Versions].

• CLEVRER: CoLlision Events for Video REpresentation and Reasoning - ICLR'20, 2020. [All Versions].

• The relationship between Precision-Recall and ROC curves - ICML'06, 2006. [All Versions].

• Distributional Generalization: A New Kind of Generalization - 2020. [All Versions].

• Language acquisition in the absence of explicit negative evidence: how important is starting small? - Cognition, 1999. [All Versions].

• Parsing video events with goal inference and intent prediction - ICCV'11, 2011. [All Versions].

• Explainable and Explicit Visual Reasoning over Scene Graphs - CVPR'19, 2019. [All Versions].

• Distributed Representations of Words and Phrases and their Compositionality - NIPS'13, 2013. [All Versions].

• Motion Reasoning for Goal-Based Imitation Learning - ICRA'20, 2020. [All Versions].

• Action Genome: Actions as Compositions of Spatio-temporal Scene Graphs - CVPR'20, 2020. [All Versions].

• Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals - NIPS'20, 2020. [All Versions].

• Something-Else: Compositional Action Recognition with Spatial-Temporal Interaction Networks - CVPR'20, 2020. [All Versions].

• Putting visual object recognition in context - CVPR'20, 2020. [All Versions].

• Multimodal Few-Shot Learning with Frozen Language Models - 2021. [All Versions].

• Describing Objects by their Attributes - CVPR'09, 2009. [All Versions].

• Panoramic Learning with A Standardized Machine Learning Formalism - 2021. [All Versions].

MIT / Commonsense Knowledgebase

• Center for Brains, Minds and Machines (CBMM) - NSF.

• Rebecca Saxe - MIT, Social Cognitive Neuroscience Laboratory (SaxeLab) - Department of Brain and Cognitive Sciences, MIT.

• Laura Schulz - MIT, Early Childhood Cognition Lab - Department of Brain and Cognitive Sciences, MIT.

Stanford / Commonsense Knowledgebase

• Tobias Gerstenberg - Stanford, Causality in Cognition Lab (CICL) - Department of Psychology, Stanford.

Princeton / Commonsense Knowledgebase

• Tania Lombrozo - Princeton, Concepts & Cognition Lab - Department of Psychology, Princeton.

UC Berkeley / Commonsense Knowledgebase

• Fei Xu - UCB, Berkeley Early Learning Lab (Xu Lab) - Department of Psychology, UCB.

• Alison Gopnik - UCB, Cognitive Development & Learning Lab (Gopnik Lab) - Department of Psychology, UCB.

• Steve Piantadosi - UCB, The computation and language lab (colala) - Department of Psychology, UCB.

• Celeste Kidd - UCB, Kidd Lab - Department of Psychology, UCB.

UCSD / Commonsense Knowledgebase

• Judith Fan - UCSD, Cognitive Tools Lab - UCSD.

• Zhuowen Tu - UCSD, Machine Learning, Perception, and Cognition Lab (mlPC) - UCSD.

• Ed Vul - UCSD, Computational Cognition Lab - UCSD.

NYU / Commonsense Knowledgebase

• Brenden Lake - NYU, Human & Machine Learning Lab (Lake Lab) - NYU.

• Todd Gureckis - NYU, Computation & Cognition Lab - NYU.

• Wei Ji Ma - NYU, Wei Ji Ma Lab - NYU.

Ulf Grenander / Commonsense Knowledgebase

• A Calculus of Ideas: A Mathematical Study of Thinking - World Scientific Publishing Company, 2012. [All Versions].

• General Pattern Theory: A Mathematical Study of Regular Structures - Oxford University Press, 1993. [All Versions].

Michael Tomasello / Commonsense Knowledgebase

• Origins of human communication - MIT Press, 2010. [All Versions].

• The cultural origins of human cognition - Havard University Press, 2000. [All Versions].

Judea Pearl / Commonsense Knowledgebase

• The Book of Why: The New Science of Cause and Effect - Basic Books, 2018. [All Versions].

• Causality: Models, Reasoning and Inference - Cambridge University Press, 2009. [All Versions].

Daniel Kahneman / Commonsense Knowledgebase

• Thinking, fast and slow - Farrar Straus Giroux, 2011. [All Versions].