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cs.CL2026
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…
cs.CL2024
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…
cs.CL2023
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…