Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

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

[BibT_eX]

[DOI]

Tiwalayo Eisape

Michael Henry Tessler

Ishita Dasgupta

Fei Sha

Sjoerd van Steenkiste

Tal Linzen

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs.

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[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Plot Twist: Multimodal Models Don't Comprehend Simple Chart Details.

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[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

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

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[DOI]

PLoS Comput. Biol., 2023

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

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[DOI]

Jackson Petty

Sjoerd van Steenkiste

CoRR, 2023

Hierarchical reinforcement learning with natural language subgoals.

[BibT_eX]

[DOI]

CoRR, 2023

Meta-Learned Models of Cognition.

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[DOI]

CoRR, 2023

Collaborating with language models for embodied reasoning.

[BibT_eX]

[DOI]

Ishita Dasgupta

Christine Kaeser-Chen

CoRR, 2023

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

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[DOI]

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.

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[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

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

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[DOI]

CoRR, 2022

Language models show human-like content effects on reasoning.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Learning to Navigate Wikipedia by Taking Random Walks.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

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[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Distinguishing rule and exemplar-based generalization in learning systems.

[BibT_eX]

[DOI]

Ishita Dasgupta

Erin Grant

Tom Griffiths

Proceedings of the International Conference on Machine Learning, 2022

Can language models learn from explanations in context?

[BibT_eX]

[DOI]

Michael Henry Tessler

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

2021

Passive attention in artificial neural networks predicts human visual selectivity.

[BibT_eX]

[DOI]

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.

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[DOI]

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

Chunking as a Rational Solution to the Speed-Accuracy Trade-off in a Serial Reaction Time Task.

[BibT_eX]

[DOI]

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

Are Convolutional Neural Networks or Transformers more like human vision?

[BibT_eX]

[DOI]

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

How does mental sorting scale?

[BibT_eX]

[DOI]

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

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

[BibT_eX]

[DOI]

CoRR, 2020

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

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[DOI]

Cogn. Sci., 2020

2019

Causal Reasoning from Meta-reinforcement Learning.

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[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

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

2018

Learning to act by integrating mental simulations and physical experiments.

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[DOI]

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

Evaluating Compositionality in Sentence Embeddings.

[BibT_eX]

[DOI]

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

2017

Amortized Hypothesis Generation.

[BibT_eX]

[DOI]

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

Markov Transitions between Attractor States in a Recurrent Neural Network.

[BibT_eX]

[DOI]

Proceedings of the 2017 AAAI Spring Symposia, 2017

Ishita Dasgupta

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