2.3k citations · 4.7k across the 88 of their papers we have counts for
15 papers · 1 filter
CLEVRER-Humans: Describing Physical and Causal Events the Human Way
Jiayuan Mao, Xuelin Yang, Xikun Zhang +2
Building machines that can reason about physical events and their causal relationships is crucial for flexible interaction with the physical world. However, most existing physical…
Hypothesis Search: Inductive Reasoning with Language Models
Ruocheng Wang, Eric Zelikman, Gabriel Poesia +3
Inductive reasoning is a core problem-solving capacity: humans can identify underlying principles from a few examples, which robustly generalize to novel scenarios. Recent work eva…
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought
Lionel Wong, Gabriel Grand, Alexander K. Lew +4
How does language inform our downstream thinking? In particular, how do humans make meaning from language--and how can we leverage a theory of linguistic meaning to build machines…
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness
Eric Zelikman, Qian Huang, Percy Liang +2
Language model training in distributed settings is limited by the communication cost of gradient exchanges. In this short note, we extend recent work from Malladi et al. (2023), us…
Understanding Social Reasoning in Language Models with Language Models
Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg +1
As Large Language Models (LLMs) become increasingly integrated into our everyday lives, understanding their ability to comprehend human mental states becomes critical for ensuring…
Strategic Reasoning with Language Models
Kanishk Gandhi, Dorsa Sadigh, Noah D. Goodman
Strategic reasoning enables agents to cooperate, communicate, and compete with other agents in diverse situations. Existing approaches to solving strategic games rely on extensive…