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Poster
in
Workshop: Foundation Model Interventions

GPT-2 Small Fine-Tuned on Logical Reasoning Summarizes Information on Punctuation Tokens

Sonakshi Chauhan · Atticus Geiger

Keywords: [ Reasoning ] [ Interpretability ] [ Causality ]


Abstract:

How is information stored and aggregated within a language model performing inference? Preliminary evidence suggests that representations of punctuation tokens might serve as ``summary points'' for information about preceding text. We add to this body of evidence by demonstrating that GPT-2 small fine-tuned on the RuleTaker logical inference dataset aggregates crucial information about rules and sentences above period tokens.

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