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ORCIDIshita Dasgupta 0001
Person information
- affiliation: Google DeepMind
- affiliation (former): Princeton University, USA
Other persons with the same name
- Ishita Dasgupta 0002 — Adobe Research, USA (and 1 more)
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2020 – today
- 2024
[c22]Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths:
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? ICML 2024- [c21]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:
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. ICML 2024 - [c20]Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen:
The Impact of Depth on Compositional Generalization in Transformer Language Models. NAACL-HLT 2024: 7239-7252 - [c19]Tiwalayo Eisape, Michael Henry Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen:
A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models. NAACL-HLT 2024: 8425-8444 - [i25]Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths:
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? CoRR abs/2402.07282 (2024) - [i24]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:
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. CoRR abs/2402.07872 (2024) - [i23]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, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young:
Scaling Instructable Agents Across Many Simulated Worlds. CoRR abs/2404.10179 (2024) - [i22]Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Dee Guo, Sreenivas Gollapudi, Ahmed Qureshi:
ReMI: A Dataset for Reasoning with Multiple Images. CoRR abs/2406.09175 (2024) - 2023
- [j2]Sreejan Kumar
, Ishita Dasgupta, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths:
Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. PLoS Comput. Biol. 19(8) (2023) - [c18]Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta:
Distilling Internet-Scale Vision-Language Models into Embodied Agents. ICML 2023: 32797-32818 - [c17]Andrew K. Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang:
Passive learning of active causal strategies in agents and language models. NeurIPS 2023 - [i21]Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta:
Distilling Internet-Scale Vision-Language Models into Embodied Agents. CoRR abs/2301.12507 (2023) - [i20]Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, Arun Ahuja, Sheila Babayan, Felix Hill, Rob Fergus:
Collaborating with language models for embodied reasoning. CoRR abs/2302.00763 (2023) - [i19]Marcel Binz, Ishita Dasgupta, Akshay Kumar Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz:
Meta-Learned Models of Cognition. CoRR abs/2304.06729 (2023) - [i18]Andrew Kyle Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang:
Passive learning of active causal strategies in agents and language models. CoRR abs/2305.16183 (2023) - [i17]Arun Ahuja, Kavya Kopparapu, Rob Fergus, Ishita Dasgupta:
Hierarchical reinforcement learning with natural language subgoals. CoRR abs/2309.11564 (2023) - [i16]Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen:
The Impact of Depth and Width on Transformer Language Model Generalization. CoRR abs/2310.19956 (2023) - [i15]Tiwalayo Eisape, Michael Henry Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen:
A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models. CoRR abs/2311.00445 (2023) - 2022
- [c16]Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill:
Can language models learn from explanations in context? EMNLP (Findings) 2022: 537-563 - [c15]Ishita Dasgupta, Erin Grant, Tom Griffiths:
Distinguishing rule and exemplar-based generalization in learning systems. ICML 2022: 4816-4830 - [c14]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:
Tell me why! Explanations support learning relational and causal structure. ICML 2022: 11868-11890 - [c13]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:
Using natural language and program abstractions to instill human inductive biases in machines. NeurIPS 2022 - [c12]Shuchen Wu, Noémi Élteto, Ishita Dasgupta, Eric Schulz:
Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking. NeurIPS 2022 - [c11]Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus:
Learning to Navigate Wikipedia by Taking Random Walks. NeurIPS 2022 - [i14]Sreejan Kumar, Ishita Dasgupta, Raja Marjieh, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths:
Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. CoRR abs/2204.01437 (2022) - [i13]Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane X. Wang, Felix Hill:
Can language models learn from explanations in context? CoRR abs/2204.02329 (2022) - [i12]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:
Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines. CoRR abs/2205.11558 (2022) - [i11]Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Antonia Creswell, Dharshan Kumaran, James L. McClelland, Felix Hill:
Language models show human-like content effects on reasoning. CoRR abs/2207.07051 (2022) - [i10]Stephanie C. Y. Chan, Ishita Dasgupta, Junkyung Kim, Dharshan Kumaran, Andrew K. Lampinen, Felix Hill:
Transformers generalize differently from information stored in context vs in weights. CoRR abs/2210.05675 (2022) - [i9]Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus:
Learning to Navigate Wikipedia by Taking Random Walks. CoRR abs/2211.00177 (2022) - 2021
- [c10]Susanne Haridi, Charley M. Wu, Ishita Dasgupta, Eric Schulz:
How does mental sorting scale? CogSci 2021 - [c9]Shikhar Tuli, Ishita Dasgupta, Erin Grant, Tom Griffiths:
Are Convolutional Neural Networks or Transformers more like human vision? CogSci 2021 - [c8]Shuchen Wu, Noémi Élteto, Ishita Dasgupta, Eric Schulz:
Chunking as a Rational Solution to the Speed-Accuracy Trade-off in a Serial Reaction Time Task. CogSci 2021 - [c7]Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths:
Meta-Learning of Structured Task Distributions in Humans and Machines. ICLR 2021 - [c6]Thomas A. Langlois, H. Charles Zhao, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby:
Passive attention in artificial neural networks predicts human visual selectivity. NeurIPS 2021: 27094-27106 - [i8]Shikhar Tuli, Ishita Dasgupta, Erin Grant, Thomas L. Griffiths:
Are Convolutional Neural Networks or Transformers more like human vision? CoRR abs/2105.07197 (2021) - [i7]Thomas A. Langlois, H. Charles Zhao, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby:
Passive attention in artificial neural networks predicts human visual selectivity. CoRR abs/2107.07013 (2021) - [i6]Ishita Dasgupta, Erin Grant, Thomas L. Griffiths:
Distinguishing rule- and exemplar-based generalization in learning systems. CoRR abs/2110.04328 (2021) - [i5]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:
Tell me why! - Explanations support learning of relational and causal structure. CoRR abs/2112.03753 (2021) - 2020
- [j1]Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman:
Analyzing Machine-Learned Representations: A Natural Language Case Study. Cogn. Sci. 44(12) (2020) - [i4]Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths:
Meta-Learning of Compositional Task Distributions in Humans and Machines. CoRR abs/2010.02317 (2020)
2010 – 2019
- 2019
- [c5]Ishita Dasgupta, Eric Schulz, Jessica B. Hamrick, Josh Tenenbaum:
Heuristics, hacks, and habits: Boundedly optimal approaches to learning, reasoning and decision making. CogSci 2019: 1-2 - [i3]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:
Causal Reasoning from Meta-reinforcement Learning. CoRR abs/1901.08162 (2019) - [i2]Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman:
Analyzing machine-learned representations: A natural language case study. CoRR abs/1909.05885 (2019) - 2018
- [c4]Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel Gershman, Noah D. Goodman:
Evaluating Compositionality in Sentence Embeddings. CogSci 2018 - [c3]Ishita Dasgupta, Kevin A. Smith, Eric Schulz, Josh Tenenbaum, Samuel Gershman:
Learning to act by integrating mental simulations and physical experiments. CogSci 2018 - [i1]Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel J. Gershman, Noah D. Goodman:
Evaluating Compositionality in Sentence Embeddings. CoRR abs/1802.04302 (2018) - 2017
- [c2]Jeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky:
Markov Transitions between Attractor States in a Recurrent Neural Network. AAAI Spring Symposia 2017 - [c1]Ishita Dasgupta, Eric Schulz, Noah D. Goodman, Samuel J. Gershman:
Amortized Hypothesis Generation. CogSci 2017
Coauthor Index
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