Jonathan D. Cohen

99 papers A* 9A 3B 13Journal 63Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Multiple-Well Framework for Human Perceptual Decision-Making. Entropy Joseph Fluegemann, Jiaqi Huang, Lena Rosendahl, Jerome R. Busemeyer, Jonathan D. Cohen
2026	J	`jnl`	The Geometry of Representational Failures in Vision Language Models. CoRR Daniele Savietto, Declan Campbell, André Panisson, Marco Nurisso, Giovanni Petri, Jonathan D. Cohen, Alan Perotti
2025	J	`jnl`	A Group Theoretic Analysis of the Symmetries Underlying Base Addition and Their Learnability by Neural Networks. CoRR Cutter Dawes, Simon N. Segert, Kamesh Krishnamurthy, Jonathan D. Cohen
2025	J	`jnl`	AI-enhanced semantic feature norms for 786 concepts. CoRR Siddharth Suresh, Kushin Mukherjee, Tyler Giallanza, Xizheng Yu, Mia Patil, Jonathan D. Cohen, Timothy T. Rogers
2025	J	`jnl`	Bound by semanticity: universal laws governing the generalization-identification tradeoff. CoRR Marco Nurisso, Jesseba Fernando, Raj Deshpande, Alan Perotti, Raja Marjieh, Steven M. Frankland, Richard L. Lewis, Taylor W. Webb, Declan Campbell, Francesco Vaccarino, Jonathan D. Cohen, Giovanni Petri
2025	J	`jnl`	Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers. CoRR Andrew Nam, Henry Conklin, Yukang Yang, Thomas L. Griffiths, Jonathan D. Cohen, Sarah-Jane Leslie
2025	A*	`conf`	Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models. ICML Yukang Yang, Declan Campbell, Kaixuan Huang, Mengdi Wang, Jonathan D. Cohen, Taylor Whittington Webb
2025	J	`jnl`	Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models. CoRR Yukang Yang, Declan Campbell, Kaixuan Huang, Mengdi Wang, Jonathan D. Cohen, Taylor W. Webb
2025	J	`jnl`	Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents: Pathways and Paradigms. CoRR Abhijit Chatterjee, Niraj K. Jha, Jonathan D. Cohen, Thomas L. Griffiths, Hongjing Lu, Diana Marculescu, Ashiqur Rasul, Keshab K. Parhi
2025	J	`jnl`	Inferring System and Optimal Control Parameters of Closed-Loop Systems from Partial Observations. CoRR Victor Geadah, Juncal Arbelaiz, Harrison Ritz, Nathaniel D. Daw, Jonathan D. Cohen, Jonathan W. Pillow
2025	J	`jnl`	Understanding Task Representations in Neural Networks via Bayesian Ablation. CoRR Andrew Nam, Declan Campbell, Thomas L. Griffiths, Jonathan D. Cohen, Sarah-Jane Leslie
2025	J	`jnl`	Visual serial processing deficits explain divergences in human and VLM reasoning. CoRR Nicholas Budny, Kia Ghods, Declan Campbell, Raja Marjieh, Amogh Joshi, Sreejan Kumar, Jonathan D. Cohen, Taylor W. Webb, Thomas L. Griffiths
2024	J	`jnl`	A Relational Inductive Bias for Dimensional Abstraction in Neural Networks. CoRR Declan Campbell, Jonathan D. Cohen
2024	A*	`conf`	Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers. ICLR Awni Altabaa, Taylor Whittington Webb, Jonathan D. Cohen, John Lafferty
2024	J	`jnl`	Erratum: Multitasking Capacity: Hardness Results and Improved Constructions. SIAM J. Discret. Math. Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner
2024	J	`jnl`	Human-Like Geometric Abstraction in Large Pre-trained Neural Networks. CoRR Declan Campbell, Sreejan Kumar, Tyler Giallanza, Thomas L. Griffiths, Jonathan D. Cohen
2024	—	`conf`	Inferring System and Optimal Control Parameters of Closed-Loop Systems from Partial Observations. CDC Victor Geadah, Juncal Arbelaiz, Harrison Ritz, Nathaniel D. Daw, Jonathan D. Cohen, Jonathan W. Pillow
2024	A*	`conf`	Slot Abstractors: Toward Scalable Abstract Visual Reasoning. ICML Shanka Subhra Mondal, Jonathan D. Cohen, Taylor Whittington Webb
2024	J	`jnl`	Slot Abstractors: Toward Scalable Abstract Visual Reasoning. CoRR Shanka Subhra Mondal, Jonathan D. Cohen, Taylor W. Webb
2024	A*	`conf`	Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem. NeurIPS Declan Campbell, Sunayana Rane, Tyler Giallanza, Nicolò De Sabbata, Kia Ghods, Amogh Joshi, Alexander Ku, Steven Frankland, Tom Griffiths, Jonathan D. Cohen, Taylor W. Webb
2024	J	`jnl`	Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem. CoRR Declan Campbell, Sunayana Rane, Tyler Giallanza, Nicolò De Sabbata, Kia Ghods, Amogh Joshi, Alexander Ku, Steven M. Frankland, Thomas L. Griffiths, Jonathan D. Cohen, Taylor W. Webb
2023	J	`jnl`	A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks. CoRR Ryan Pyle, Sebastian Musslick, Jonathan D. Cohen, Ankit B. Patel
2023	J	`jnl`	Abstractors: Transformer Modules for Symbolic Message Passing and Relational Reasoning. CoRR Awni Altabaa, Taylor W. Webb, Jonathan D. Cohen, John Lafferty
2023	J	`jnl`	Beyond Transformers for Function Learning. CoRR Simon N. Segert, Jonathan D. Cohen
2023	J	`jnl`	Determinantal Point Process Attention Over Grid Codes Supports Out of Distribution Generalization. CoRR Shanka Subhra Mondal, Steven Frankland, Taylor W. Webb, Jonathan D. Cohen
2023	J	`jnl`	Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. PLoS Comput. Biol. Sreejan Kumar, Ishita Dasgupta, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths
2023	J	`jnl`	Learning to reason over visual objects. CoRR Shanka Subhra Mondal, Taylor Whittington Webb, Jonathan D. Cohen
2023	J	`jnl`	Quantum Cognitive Modeling: New Applications and Systems Research Directions. CoRR Raghavendra Pradyumna Pothukuchi, Leon Lufkin, Yu Jun Shen, Alejandro Simon, Rome Thorstenson, Bernardo Eilert Trevisan, Michael Tu, Mudi Yang, Ben Foxman, Viswanatha Srinivas Pothukuchi, Gunnar Epping, Bryant J. Jongkees, Thi Ha Kyaw, Jerome R. Busemeyer, Jonathan D. Cohen, Abhishek Bhattacharjee
2023	A*	`conf`	Systematic Visual Reasoning through Object-Centric Relational Abstraction. NeurIPS Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen
2023	J	`jnl`	Systematic Visual Reasoning through Object-Centric Relational Abstraction. CoRR Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen
2023	J	`jnl`	The Relational Bottleneck as an Inductive Bias for Efficient Abstraction. CoRR Taylor W. Webb, Steven M. Frankland, Awni Altabaa, Kamesh Krishnamurthy, Declan Campbell, Jacob L. Russin, Randall C. O'Reilly, John Lafferty, Jonathan D. Cohen
2022	J	`jnl`	A Self-Supervised Framework for Function Learning and Extrapolation. Trans. Mach. Learn. Res. Simon N. Segert, Jonathan D. Cohen
2022	J	`jnl`	Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large-Scale Text Corpora. Cogn. Sci. Marius Catalin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole M. Beckage, Jonathan D. Cohen
2022	J	`jnl`	Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. CoRR Sreejan Kumar, Ishita Dasgupta, Raja Marjieh, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths
2022	A	`conf`	Distill: Domain-Specific Compilation for Cognitive Models. CGO Ján Veselý, Raghavendra Pradyumna Pothukuchi, Ketaki Joshi, Samyak Gupta, Jonathan D. Cohen, Abhishek Bhattacharjee
2022	J	`jnl`	Modularity benefits reinforcement learning agents with competing homeostatic drives. CoRR Zack Dulberg, Rachit Dubey, Isabel M. Berwian, Jonathan D. Cohen
2022	J	`jnl`	RT-Cloud: A cloud-based software framework to simplify and standardize real-time fMRI. NeuroImage Grant Wallace, Stephen Polcyn, Paula P. Brooks, Anne C. Mennen, Ke Zhao, Paul S. Scotti, Sebastian Michelmann, Kai Li, Nicholas B. Turk-Browne, Jonathan D. Cohen, Kenneth A. Norman
2022	J	`jnl`	Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines. CoRR Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Nathaniel D. Daw, Jonathan D. Cohen, Karthik Narasimhan, Thomas L. Griffiths
2022	A*	`conf`	Using natural language and program abstractions to instill human inductive biases in machines. NeurIPS Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Jonathan D. Cohen, Nathaniel D. Daw, Karthik Narasimhan, Tom Griffiths
2021	J	`jnl`	A Self-Supervised Framework for Function Learning and Extrapolation. CoRR Simon N. Segert, Jonathan D. Cohen
2021	J	`jnl`	Cognac: Domain-Specific Compilation for Cognitive Models. CoRR Ján Veselý, Raghavendra Pradyumna Pothukuchi, Ketaki Joshi, Samyak Gupta, Jonathan D. Cohen, Abhishek Bhattacharjee
2021	J	`jnl`	Control of mental representations in human planning. CoRR Mark K. Ho, David Abel, Carlos G. Correa, Michael L. Littman, Jonathan D. Cohen, Thomas L. Griffiths
2021	A*	`conf`	Emergent Symbols through Binding in External Memory. ICLR Taylor Whittington Webb, Ishan Sinha, Jonathan D. Cohen
2021	A*	`conf`	Meta-Learning of Structured Task Distributions in Humans and Machines. ICLR Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths
2020	J	`jnl`	A Memory-Augmented Neural Network Model of Abstract Rule Learning. CoRR Ishan Sinha, Taylor W. Webb, Jonathan D. Cohen
2020	J	`jnl`	Emergent Symbols through Binding in External Memory. CoRR Taylor W. Webb, Ishan Sinha, Jonathan D. Cohen
2020	J	`jnl`	Learning Canonical Transformations. CoRR Zachary Dulberg, Jonathan D. Cohen
2020	J	`jnl`	Learning Representations that Support Extrapolation. CoRR Taylor W. Webb, Zachary Dulberg, Steven M. Frankland, Alexander A. Petrov, Randall C. O'Reilly, Jonathan D. Cohen
2020	B	`conf`	Mental effort: One construct, many faces? CogSci Sebastian Musslick, Maria Wirzberger, Ivan Grahek, Laura Bustamante, Amitai Shenhav, Jonathan D. Cohen
2020	J	`jnl`	Meta-Learning of Compositional Task Distributions in Humans and Machines. CoRR Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths
2020	J	`jnl`	Multitasking Capacity: Hardness Results and Improved Constructions. SIAM J. Discret. Math. Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner, Alexander Y. Ku
2020	J	`jnl`	Navigating the Trade-Off between Multi-Task Learning and Learning to Multitask in Deep Neural Networks. CoRR Sachin Ravi, Sebastian Musslick, Maia Hamin, Theodore L. Willke, Jonathan D. Cohen
2020	A*	`conf`	People Do Not Just Plan, They Plan to Plan. AAAI Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths
2020	J	`jnl`	The Efficiency of Human Cognition Reflects Planned Information Processing. CoRR Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths
2019	B	`conf`	A Mechanistic Account of Constraints on Control-Dependent Processing: Shared Representation, Conflict and Persistence. CogSci Sebastian Musslick, Jonathan D. Cohen
2019	B	`conf`	Asymmetric Switch Costs as a Function of Task Strength. CogSci Markus Spitzer, Sebastian Musslick, Michael Shvartsman, Amitai Shenhav, Jonathan D. Cohen
2019	J	`jnl`	Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large-Scale Text Corpora. CoRR Marius Catalin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole Beckage, Jonathan D. Cohen
2019	B	`conf`	Decomposing Individual Differences in Cognitive Control: A Model-Based Approach. CogSci Sebastian Musslick, Jonathan D. Cohen, Amitai Shenhav
2019	B	`conf`	Stability-Flexibility Dilemma in Cognitive Control: A Dynamical System Perspective. CogSci Sebastian Musslick, Anastasia S. Bizyaeva, Shamay Agaron, Naomi Ehrich Leonard, Jonathan D. Cohen
2019	B	`conf`	Understanding interactions amongst cognitive control, learning and representation. CogSci Sebastian Musslick, Abigail Novick Hoskin, Taylor W. Webb, Steven Frankland, Jonathan D. Cohen, Rebecca L. Jackson, Matthew A. Lambon Ralph, Lang Chen, Timothy T. Rogers, Randall C. O'Reilly, Alexander A. Petrov
2018	B	`conf`	Constraints associated with cognitive control and the stability-flexibility dilemma. CogSci Sebastian Musslick, Seong Jun Jang, Michael Shvartsman, Amitai Shenhav, Jonathan D. Cohen
2018	B	`conf`	Efficiency of learning vs. processing: Towards a normative theory of multitasking. CogSci Yotam Sagiv, Sebastian Musslick, Yael Niv, Jonathan D. Cohen
2018	B	`conf`	Estimating the costs of cognitive control from task performance: theoretical validation and potential pitfalls. CogSci Sebastian Musslick, Jonathan D. Cohen, Amitai Shenhav
2018	A	`conf`	Matrix-normal models for fMRI analysis. AISTATS Michael Shvartsman, Narayanan Sundaram, Mikio Aoi, Adam Charles, Theodore L. Willke, Jonathan D. Cohen
2018	J	`jnl`	Multitasking Capacity: Hardness Results and Improved Constructions. CoRR Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner, Alexander Y. Ku
2017	B	`conf`	A Formal Approach to Modeling the Cost of Cognitive Control. CogSci Kayhan Özcimder, Biswadip Dey, Sebastian Musslick, Giovanni Petri, Nesreen K. Ahmed, Theodore L. Willke, Jonathan D. Cohen
2017	—	`conf`	A graph-theoretic approach to multitasking. NIPS Noga Alon, Daniel Reichman, Igor Shinkar, Tal Wagner, Sebastian Musslick, Jonathan D. Cohen, Tom Griffiths, Biswadip Dey, Kayhan Özcimder
2017	B	`conf`	Adaptive response priors in context-dependent decision-making. CogSci Olga Lositsky, Michael Shvartsman, Robert C. Wilson, Jonathan D. Cohen
2017	B	`conf`	Multitasking Capability Versus Learning Efficiency in Neural Network Architectures. CogSci Sebastian Musslick, Andrew Saxe, Kayhan Özcimder, Biswadip Dey, Greg Henselman, Jonathan D. Cohen
2017	J	`jnl`	Noise correlations in the human brain and their impact on pattern classification. PLoS Comput. Biol. Vikranth R. Bejjanki, Rava Azeredo da Silveira, Jonathan D. Cohen, Nicholas B. Turk-Browne
2016	J	`jnl`	A Graph-Theoretic Approach to Multitasking. CoRR Jonathan D. Cohen, Biswadip Dey, Tom Griffiths, Sebastian Musslick, Kayhan Özcimder, Daniel Reichman, Igor Shinkar, Tal Wagner
2016	B	`conf`	Controlled vs. Automatic Processing: A Graph-Theoretic Approach to the Analysis of Serial vs. Parallel Processing in Neural Network Architectures. CogSci Sebastian Musslick, Biswadip Dey, Kayhan Özcimder, Md. Mostofa Ali Patwary, Theodore L. Willke, Jonathan D. Cohen
2016	—	`conf`	Real-time full correlation matrix analysis of fMRI data. IEEE BigData Yida Wang, Bryn Keller, Mihai Capota, Michael J. Anderson, Narayanan Sundaram, Jonathan D. Cohen, Kai Li, Nicholas B. Turk-Browne, Theodore L. Willke
2015	—	`conf`	A Theory of Decision Making Under Dynamic Context. NIPS Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen
2015	A	`conf`	Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors. SC Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Theodore L. Willke
2014	—	`conf`	Hierarchical topographic factor analysis. PRNI Jeremy R. Manning, Rajesh Ranganath, Waitsang Keung, Nicholas B. Turk-Browne, Jonathan D. Cohen, Kenneth A. Norman, David M. Blei
2014	J	`jnl`	Optimality and Some of Its Discontents: Successes and Shortcomings of Existing Models for Binary Decisions. Top. Cogn. Sci. Philip Holmes, Jonathan D. Cohen
2014	J	`jnl`	The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers. Cogn. Sci. Matthew M. Botvinick, Jonathan D. Cohen
2013	J	`jnl`	Confounds in multivariate pattern analysis: Theory and rule representation case study. NeuroImage Michael T. Todd, Leigh E. Nystrom, Jonathan D. Cohen
2012	J	`jnl`	A Decision Task in a Social Context: Human Experiments, Models, and Analyses of Behavioral Data. Proc. IEEE Andrea Nedic, Damon Tomlin, Philip Holmes, Deborah A. Prentice, Jonathan D. Cohen
2011	J	`jnl`	Errors of interpretation and modeling: A reply to Grinband et al. NeuroImage Nick Yeung, Jonathan D. Cohen, Matthew M. Botvinick
2011	J	`jnl`	Parametric Manipulation of the Conflict Signal and Control-state Adaptation. J. Cogn. Neurosci. Sarah E. Forster, Cameron S. Carter, Jonathan D. Cohen, Raymond Y. Cho
2009	J	`jnl`	Sequential Effects in Two-Choice Reaction Time Tasks: Decomposition and Synthesis of Mechanisms. Neural Comput. Juan Gao, KongFatt Wong-Lin, Philip Holmes, Patrick Simen, Jonathan D. Cohen
2008	J	`jnl`	A Neural Network Model of the Eriksen Task: Reduction, Analysis, and Data Fitting. Neural Comput. Yuan Sophie Liu, Philip Holmes, Jonathan D. Cohen
2008	—	`conf`	A simple decision task in a social context: Experiments, a model, and preliminary analyses of behavioral data. CDC Andrea Nedic, Damon Tomlin, Philip Holmes, Deborah A. Prentice, Jonathan D. Cohen
2008	—	`conf`	Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement. NIPS Michael T. Todd, Yael Niv, Jonathan D. Cohen
2008	J	`jnl`	Optimization of Decision Making in Multilayer Networks: The Role of Locus Coeruleus. Neural Comput. Eric Shea-Brown, Mark S. Gilzenrat, Jonathan D. Cohen
2008	—	`conf`	Sequential effects: Superstition or rational behavior? NIPS Angela J. Yu, Jonathan D. Cohen
2006	J	`jnl`	Rapid decision threshold modulation by reward rate in a neural network. Neural Networks Patrick Simen, Jonathan D. Cohen, Philip Holmes
2005	—	`conf`	An exploration-exploitation model based on norepinepherine and dopamine activity. NIPS Samuel M. McClure, Mark S. Gilzenrat, Jonathan D. Cohen
2005	J	`jnl`	Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Philip Holmes, Eric Shea-Brown, Jeff Moehlis, Rafal Bogacz, Juan Gao, Gary Aston-Jones, Ed Clayton, Janusz Rajkowski, Jonathan D. Cohen
2005	J	`jnl`	Simple Neural Networks that Optimize Decisions. Int. J. Bifurc. Chaos Eric Brown, Juan Gao, Philip Holmes, Rafal Bogacz, Mark S. Gilzenrat, Jonathan D. Cohen
2004	J	`jnl`	The neural correlates of theory of mind within interpersonal interactions. NeuroImage James K. Rilling, Alan G. Sanfey, Jessica A. Aronson, Leigh E. Nystrom, Jonathan D. Cohen
2003	J	`jnl`	Fiswidgets - A graphical computing environment for neuroimaging analysis. Neuroinformatics Kate Fissell, Eugene Tseytlin, Daniel Cunningha, Karthickeyan Iyer, Cameron S. Carter, Walter Schneider, Jonathan D. Cohen
2002	J	`jnl`	Hyperscanning: Simultaneous fMRI during Linked Social Interactions. NeuroImage P. Read Montague, Gregory S. Berns, Jonathan D. Cohen, Samuel M. McClure, Giuseppe Pagnoni, Mukesh Dhamala, Michael C. Wiest, Igor Karpov, Richard D. King, Nathan Apple, Ronald E. Fisher
2002	J	`jnl`	Simplified dynamics in a model of noradrenergic modulation of cognitive performance. Neural Networks Mark S. Gilzenrat, Benjamin D. Holmes, Janusz Rajkowski, Gary Aston-Jones, Jonathan D. Cohen
2001	J	`jnl`	Anterior Cingulate Cortex, Conflict Monitoring, and Levels of Processing. NeuroImage Vincent van Veen, Jonathan D. Cohen, Matthew M. Botvinick, V. Andrew Stenger, Cameron S. Carter
1994	—	`conf`	A Computational Model of Prefrontal Cortex Function. NIPS Todd S. Braver, Jonathan D. Cohen, David Servan-Schreiber
1989	—	`conf`	The Effect of Catecholamines on Performance: From Unit to System Behavior. NIPS David Servan-Schreiber, Harry Printz, Jonathan D. Cohen