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cs.CL2026
Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs
Vishal Pramanik, Maisha Maliha, Nathaniel D. Bastian +1
Attribution methods seek to explain language model predictions by quantifying the contribution of input tokens to generated outputs. However, most existing techniques are designed…
cs.CL2025
Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding
Trilok Padhi, Ramneet Kaur, Adam D. Cobb +7
We introduce a novel approach for calibrating uncertainty quantification (UQ) tailored for multi-modal large language models (LLMs). Existing state-of-the-art UQ methods rely on co…