LLM evaluation pipelines often have many candidate judges: general LLM-as-a-judge prompts, reward models, safety classifiers, confidence variants, and task-specific verifiers. The deployment question is not only which judge is best, but which judges should be called, on which examples, and when panel construction shoul...
This work revisits on-policy Reverse Kullback-Leibler distillation and decomposes its objective into a teacher-fitting term and a student-entropy term, without introducing an explicit FKL branch, and proposes Adaptive Entropy Distillation (AED), which uses the teacher's entropy to dynamically calibrate token-level imit...
Shizheng Li, Zhiyu Shen, Yu-Yin Lu et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.