3 papers
cs.LG2026
Rethinking Reverse KL as Adaptive Entropy Distillation
Shizhen Li, Zhiyu Shen, Yuyin Lu +4
Knowledge distillation (KD) is widely used to transfer the capabilities of large language models (LLMs) to smaller students, but existing objectives often struggle to balance faith…
cs.CL2026
Stopping and Routing LLM Judge Panels
Bin Zhu, Yi Xie, Yanghui Rao
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…
cs.CL2024
IterSelectTune: An Iterative Training Framework for Efficient Instruction-Tuning Data Selection
Jielin Song, Siyu Liu, Bin Zhu +1
As large language models (LLMs) continue to advance, instruction tuning has become critical for improving their ability to generate accurate and contextually appropriate responses.…