Markov Transitions between Attractor States in a Recurrent Neural Network. - Jeremy Bernstein; Ishita Dasgupta 001; David Rolnick; Haim Sompolinsky (AAAI Spring Symposia, 2017)

Amortized Hypothesis Generation. - Ishita Dasgupta 001; Eric Schulz; Noah D. Goodman; Samuel J. Gershman (CogSci, 2017)

Evaluating Compositionality in Sentence Embeddings. - Ishita Dasgupta 001; Demi Guo; Andreas Stuhlmüller; Samuel Gershman; Noah D. Goodman (CogSci, 2018)

Learning to act by integrating mental simulations and physical experiments. - Ishita Dasgupta 001; Kevin A. Smith 001; Eric Schulz; Josh Tenenbaum 001; Samuel Gershman (CogSci, 2018)

Heuristics, hacks, and habits: Boundedly optimal approaches to learning, reasoning and decision making. - Ishita Dasgupta 001; Eric Schulz; Jessica B. Hamrick; Josh Tenenbaum 001 (CogSci, 2019)

Causal Reasoning from Meta-reinforcement Learning. - Ishita Dasgupta 001; Jane X. Wang; Silvia Chiappa; Jovana Mitrovic; Pedro A. Ortega; David Raposo; Edward Hughes 001; Peter W. Battaglia; Matthew M. Botvinick; Zeb Kurth-Nelson (CoRR, 2019)

Analyzing Machine-Learned Representations: A Natural Language Case Study. - Ishita Dasgupta 001; Demi Guo; Samuel J. Gershman; Noah D. Goodman (Cogn. Sci., 2020)

Meta-Learning of Compositional Task Distributions in Humans and Machines. - Sreejan Kumar; Ishita Dasgupta 001; Jonathan D. Cohen 003; Nathaniel D. Daw; Thomas L. Griffiths 001 (CoRR, 2020)

How does mental sorting scale? - Susanne Haridi; Charley M. Wu; Ishita Dasgupta 001; Eric Schulz (CogSci, 2021)

Are Convolutional Neural Networks or Transformers more like human vision? - Shikhar Tuli; Ishita Dasgupta 001; Erin Grant; Tom Griffiths 001 (CogSci, 2021)

Chunking as a Rational Solution to the Speed-Accuracy Trade-off in a Serial Reaction Time Task. - Shuchen Wu; Noémi Élteto; Ishita Dasgupta 001; Eric Schulz (CogSci, 2021)

Meta-Learning of Structured Task Distributions in Humans and Machines. - Sreejan Kumar; Ishita Dasgupta 001; Jonathan D. Cohen 003; Nathaniel D. Daw; Thomas L. Griffiths 001 (ICLR, 2021)

Passive attention in artificial neural networks predicts human visual selectivity. - Thomas A. Langlois; H. Charles Zhao; Erin Grant; Ishita Dasgupta 001; Thomas L. Griffiths 001; Nori Jacoby (NeurIPS, 2021)

Can language models learn from explanations in context? - Andrew K. Lampinen; Ishita Dasgupta 001; Stephanie C. Y. Chan; Kory W. Mathewson; Michael Henry Tessler; Antonia Creswell; James L. McClelland; Jane Wang 001; Felix Hill (EMNLP (Findings), 2022)

Distinguishing rule and exemplar-based generalization in learning systems. - Ishita Dasgupta 001; Erin Grant; Tom Griffiths 001 (ICML, 2022)

Tell me why! Explanations support learning relational and causal structure. - Andrew K. Lampinen; Nicholas A. Roy; Ishita Dasgupta 001; Stephanie C. Y. Chan; Allison C. Tam; James L. McClelland; Chen Yan; Adam Santoro; Neil C. Rabinowitz; Jane X. Wang; Felix Hill (ICML, 2022)

Using natural language and program abstractions to instill human inductive biases in machines. - Sreejan Kumar; Carlos G. Correa; Ishita Dasgupta 001; Raja Marjieh; Michael Y. Hu; Robert D. Hawkins; Jonathan D. Cohen 003; Nathaniel D. Daw; Karthik Narasimhan; Tom Griffiths 001 (NeurIPS, 2022)

Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking. - Shuchen Wu; Noémi Élteto; Ishita Dasgupta 001; Eric Schulz (NeurIPS, 2022)

Learning to Navigate Wikipedia by Taking Random Walks. - Manzil Zaheer; Kenneth Marino; Will Grathwohl; John Schultz; Wendy Shang; Sheila Babayan; Arun Ahuja; Ishita Dasgupta 001; Christine Kaeser-Chen; Rob Fergus (NeurIPS, 2022)

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. - Sreejan Kumar; Ishita Dasgupta 001; Raja Marjieh; Nathaniel D. Daw; Jonathan D. Cohen 003; Thomas L. Griffiths 001 (CoRR, 2022)

Language models show human-like content effects on reasoning. - Ishita Dasgupta 001; Andrew K. Lampinen; Stephanie C. Y. Chan; Antonia Creswell; Dharshan Kumaran; James L. McClelland; Felix Hill (CoRR, 2022)

Transformers generalize differently from information stored in context vs in weights. - Stephanie C. Y. Chan; Ishita Dasgupta 001; Junkyung Kim; Dharshan Kumaran; Andrew K. Lampinen; Felix Hill (CoRR, 2022)

Distilling Internet-Scale Vision-Language Models into Embodied Agents. - Theodore R. Sumers; Kenneth Marino; Arun Ahuja; Rob Fergus; Ishita Dasgupta 001 (ICML, 2023)

Passive learning of active causal strategies in agents and language models. - Andrew K. Lampinen; Stephanie C. Y. Chan; Ishita Dasgupta 001; Andrew J. Nam; Jane X. Wang (NeurIPS, 2023)

Collaborating with language models for embodied reasoning. - Ishita Dasgupta 001; Christine Kaeser-Chen; Kenneth Marino; Arun Ahuja; Sheila Babayan; Felix Hill; Rob Fergus (CoRR, 2023)

Meta-Learned Models of Cognition. - Marcel Binz; Ishita Dasgupta 001; Akshay K. Jagadish; Matthew M. Botvinick; Jane X. Wang; Eric Schulz (CoRR, 2023)

Hierarchical reinforcement learning with natural language subgoals. - Arun Ahuja; Kavya Kopparapu; Rob Fergus; Ishita Dasgupta 001 (CoRR, 2023)

The Impact of Depth and Width on Transformer Language Model Generalization. - Jackson Petty; Sjoerd van Steenkiste; Ishita Dasgupta 001; Fei Sha; Dan Garrette; Tal Linzen (CoRR, 2023)

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. - Sreejan Kumar; Ishita Dasgupta 001; Nathaniel D. Daw; Jonathan D. Cohen 003; Thomas L. Griffiths 001 (PLoS Comput. Biol., 2023)

Plot Twist: Multimodal Models Don't Comprehend Simple Chart Details. - Yasaman Razeghi; Ishita Dasgupta 001; Fangyu Liu; Vinay Ramasesh; Sameer Singh 001 (EMNLP (Findings), 2024)

How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? - Ryan Liu 001; Theodore R. Sumers; Ishita Dasgupta 001; Thomas L. Griffiths 001 (ICML, 2024)

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. - Soroush Nasiriany; Fei Xia 002; Wenhao Yu 003; Ted Xiao; Jacky Liang; Ishita Dasgupta 001; Annie Xie; Danny Driess; Ayzaan Wahid; Zhuo Xu; Quan Vuong; Tingnan Zhang; et al. (ICML, 2024)

A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models. - Tiwalayo Eisape; Michael Henry Tessler; Ishita Dasgupta 001; Fei Sha; Sjoerd van Steenkiste; Tal Linzen (NAACL-HLT, 2024)

The Impact of Depth on Compositional Generalization in Transformer Language Models. - Jackson Petty; Sjoerd van Steenkiste; Ishita Dasgupta 001; Fei Sha; Dan Garrette; Tal Linzen (NAACL-HLT, 2024)

ReMI: A Dataset for Reasoning with Multiple Images. - Mehran Kazemi; Nishanth Dikkala; Ankit Anand; Petar Devic; Ishita Dasgupta 001; Fangyu Liu; Bahare Fatemi; Pranjal Awasthi; Sreenivas Gollapudi; Dee Guo; Ahmed Qureshi (NeurIPS, 2024)

Scaling Instructable Agents Across Many Simulated Worlds. - SIMA Team; Maria Abi Raad; Arun Ahuja; Catarina Barros; Frederic Besse; Andrew Bolt; Adrian Bolton; Bethanie Brownfield; Gavin Buttimore; Max Cant; Sarah Chakera; Stephanie C. Y. Chan; et al. (CoRR, 2024)

ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs. - Andrew Liu; Henry Prior; Gargi Balasubramaniam; Rivka Moroshko; Amir Zait; Ilia Labzovsky; Danny Karmon; Ishita Dasgupta 001; Kim Stachenfeld; Kenneth Marino (ICLR, 2025)

The in-context inductive biases of vision-language models differ across modalities. - Kelsey Allen; Ishita Dasgupta 001; Eliza Kosoy; Andrew K. Lampinen (CoRR, 2025)

Decoupling the components of geometric understanding in Vision Language Models. - Eliza Kosoy; Annya Dahmani; Andrew K. Lampinen; Iulia M. Comsa; Soojin Jeong; Ishita Dasgupta 001; Kelsey Allen (CoRR, 2025)

Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility. - Michael A. Lepori; Jennifer Hu 001; Ishita Dasgupta 001; Roma Patel; Thomas Serre; Ellie Pavlick (CoRR, 2025)