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arXiv Computation and Language By Brandon Colelough, Davis Bartels, Madeline Bittner, Dina Demner-Fushman

MechaTerp-TRACE: A Novel Approach for Component Ablation Analysis in Language Models

Read the original on arXiv Computation and Language →

MechaTerp-TRACE is a new framework that systematically ablates individual components of language models to measure their causal contribution to producing a named entity. By applying TRACE to thirteen instruction‑tuned dense decoder models, the study finds that a small set of positionally fixed components consistently carry the most influence across models and prompts, while the remaining support is evenly distributed. This suggests that entity knowledge is largely embedded in generic generation machinery rather than in isolated, findable components.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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