4 papers
Shared circuits predict whether LLMs generalize across formats in arithmetic reasoning
Andrea Gregor de Varda, Sana Pandey, Pengrui Han +2
In many forms of reasoning, including arithmetic reasoning, generalizing across superficial changes in input format is effortless for humans: anyone who can solve 2+5 can also solv…
Modular Cognitive Architecture Emerges in Large Language Models
Pengrui Han, Jacob Andreas, Evelina Fedorenko +1
The human brain exhibits a striking degree of functional specialization, with distinct networks supporting language, formal reasoning, reasoning about other minds, and reasoning ab…
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling
Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
Today's most accurate language models are trained on orders of magnitude more language data than human language learners receive - but with no supervision from other sensory modali…
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes
Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas
Modern neural language models (LMs) are powerful tools for modeling human sentence production and comprehension, and their internal representations are remarkably well-aligned with…