exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies.
PeerJ Comput. Sci., 2024
Quantifying Knowledge Distillation Using Partial Information Decomposition.
CoRR, 2024
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse.
CoRR, 2024
Adaptive Language-Guided Abstraction from Contrastive Explanations.
CoRR, 2024
Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience.
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CoRR, 2024
Modulating Language Model Experiences through Frictions.
CoRR, 2024
Quantifying Spuriousness of Biased Datasets Using Partial Information Decomposition.
CoRR, 2024
Large Language Models Assume People are More Rational than We Really are.
CoRR, 2024
Representational Alignment Supports Effective Machine Teaching.
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CoRR, 2024
Analyzing the Roles of Language and Vision in Learning from Limited Data.
CoRR, 2024
A Rational Analysis of the Speech-to-Song Illusion.
CoRR, 2024
Measuring Implicit Bias in Explicitly Unbiased Large Language Models.
CoRR, 2024
Learning Human-like Representations to Enable Learning Human Values.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Learning with Language-Guided State Abstractions.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Preference-Conditioned Language-Guided Abstraction.
Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024
Characterizing Similarities and Divergences in Conversational Tones in Humans and LLMs by Sampling with People.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Pushing the Limits of Learning from Limited Data.
Proceedings of the AAAI 2024 Spring Symposium Series, 2024
Concept Alignment as a Prerequisite for Value Alignment.
CoRR, 2023
Dimensions of Disagreement: Unpacking Divergence and Misalignment in Cognitive Science and Artificial Intelligence.
CoRR, 2023
On the informativeness of supervision signals.
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Alignment with human representations supports robust few-shot learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Analyzing Diffusion as Serial Reproduction.
Proceedings of the International Conference on Machine Learning, 2023
End-to-End Learnable Masks With Differentiable Indexing.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023
Words are all you need? Language as an approximation for human similarity judgments.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Around the world in 60 words: A generative vocabulary test for online research.
Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023
What Language Reveals about Perception: Distilling Psychophysical Knowledge from Large Language Models.
Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023
Large language models meet cognitive science: LLMs as tools, models, and participants.
Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023
Human Uncertainty in Concept-Based AI Systems.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023
On the Informativeness of Supervision Signals.
CoRR, 2022
Words are all you need? Capturing human sensory similarity with textual descriptors.
CoRR, 2022
Predicting Human Similarity Judgments Using Large Language Models.
Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022
Can Humans Do Less-Than-One-Shot Learning?
Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022
Playing the Lottery of a Lifetime: The Effect of Socially Induced Aspiration on Q-Learning Agents.
Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022
Learning From Almost No Data.
PhD thesis, 2021
Optimal 1-NN prototypes for pathological geometries.
PeerJ Comput. Sci., 2021
Soft-Label Dataset Distillation and Text Dataset Distillation.
Proceedings of the International Joint Conference on Neural Networks, 2021
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes.
Proceedings of the International Joint Conference on Neural Networks, 2021
SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract).
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
'Less Than One'-Shot Learning: Learning N Classes From M < N Samples.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
SecDD: Efficient and Secure Method for Remotely Training Neural Networks.
CoRR, 2020
Pay attention and you won't lose it: a deep learning approach to sequence imputation.
PeerJ Comput. Sci., 2019
Improving Dataset Distillation.
CoRR, 2019
Deep Learning for System Trace Restoration.
Proceedings of the International Joint Conference on Neural Networks, 2019