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ICLR 2026First author

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs

Vishal Pramanik, Maisha Maliha, Nathaniel D. Bastian, Sumit Kumar Jha

Understanding which input tokens influence a language model’s predictions through second-order attribution.

Research overview for heta
Research overview · Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs

The research question

Which input tokens shape an autoregressive model’s prediction?

Research summary

HETA uses Hessian-enhanced attribution to examine token-level influence. The work connects model-internal analysis with explanations of autoregressive language-model predictions.

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