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cs.CL2026
PRISM: A Geometric Risk Bound that Decomposes Drift into Scale, Shape, and Head
Chieh-Yen Lin, Shao-Hua Sun
Comparing post-training LLM variants, such as quantized, LoRA-adapted, and distilled models, requires a diagnostic that identifies how a variant has drifted, not only whether it ha…
cs.CL2026
On Calibration of Large Language Models: From Response To Capability
Sin-Han Yang, Cheng-Kuang Wu, Chieh-Yen Lin +3
Large language models (LLMs) are widely deployed as general-purpose problem solvers, making accurate confidence estimation critical for reliable use. Prior work on LLM calibration…