Ishita Dasgupta

According to our database, Ishita Dasgupta authored at least 30 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs.

Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter

CoRR, 2024

How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?

Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths

CoRR, 2024

2023

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning.

Sreejan Kumar, Ishita Dasgupta, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths

PLoS Comput. Biol., 2023

A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models.

Tiwalayo Eisape, Michael Henry Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen

CoRR, 2023

The Impact of Depth and Width on Transformer Language Model Generalization.

Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen

CoRR, 2023

Hierarchical reinforcement learning with natural language subgoals.

Arun Ahuja, Kavya Kopparapu, Rob Fergus, Ishita Dasgupta

CoRR, 2023

Meta-Learned Models of Cognition.

Marcel Binz, Ishita Dasgupta, Akshay Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz

CoRR, 2023

Collaborating with language models for embodied reasoning.

Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, Arun Ahuja, Sheila Babayan, Felix Hill, Rob Fergus

CoRR, 2023

Passive learning of active causal strategies in agents and language models.

Andrew K. Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distilling Internet-Scale Vision-Language Models into Embodied Agents.

Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta

Proceedings of the International Conference on Machine Learning, 2023

2022

Transformers generalize differently from information stored in context vs in weights.

Stephanie C. Y. Chan, Ishita Dasgupta, Junkyung Kim, Dharshan Kumaran, Andrew K. Lampinen, Felix Hill

CoRR, 2022

Language models show human-like content effects on reasoning.

Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Antonia Creswell, Dharshan Kumaran, James L. McClelland, Felix Hill

CoRR, 2022

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning.

Sreejan Kumar, Ishita Dasgupta, Raja Marjieh, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths

CoRR, 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, Christine Kaeser-Chen, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking.

Shuchen Wu, Noémi Élteto, Ishita Dasgupta, Eric Schulz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Using natural language and program abstractions to instill human inductive biases in machines.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Tell me why! Explanations support learning relational and causal structure.

Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill

Proceedings of the International Conference on Machine Learning, 2022

Distinguishing rule and exemplar-based generalization in learning systems.

Ishita Dasgupta, Erin Grant, Tom Griffiths

Proceedings of the International Conference on Machine Learning, 2022

Can language models learn from explanations in context?

Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Are Convolutional Neural Networks or Transformers more like human vision?

Shikhar Tuli, Ishita Dasgupta, Erin Grant, Thomas L. Griffiths

CoRR, 2021

Passive attention in artificial neural networks predicts human visual selectivity.

Thomas A. Langlois, H. Charles Zhao, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-Learning of Structured Task Distributions in Humans and Machines.

Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Meta-Learning of Compositional Task Distributions in Humans and Machines.

Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths

CoRR, 2020

Analyzing Machine-Learned Representations: A Natural Language Case Study.

Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman

Cogn. Sci., 2020

2019

Causal Reasoning from Meta-reinforcement Learning.

Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson

CoRR, 2019

Heuristics, hacks, and habits: Boundedly optimal approaches to learning, reasoning and decision making.

Ishita Dasgupta, Eric Schulz, Jessica B. Hamrick, Josh Tenenbaum

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018

Learning to act by integrating mental simulations and physical experiments.

Ishita Dasgupta, Kevin A. Smith, Eric Schulz, Josh Tenenbaum, Samuel Gershman

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

Evaluating Compositionality in Sentence Embeddings.

Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel Gershman, Noah D. Goodman

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017

Amortized Hypothesis Generation.

Ishita Dasgupta, Eric Schulz, Noah D. Goodman, Samuel J. Gershman

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Markov Transitions between Attractor States in a Recurrent Neural Network.

Jeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky

Proceedings of the 2017 AAAI Spring Symposia, 2017