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cs.LG2026
CODEBLOCK: Learning to Supervise Code at the Right Granularity
Zhijie Deng, Ling Li, Jinlong Pang +5
Supervised fine-tuning of code LLMs typically applies uniform cross-entropy loss to all response tokens, implicitly assuming that every token provides equally useful learning signa…
cs.AI2026
Small-Margin Preferences Still Matter-If You Train Them Right
Jinlong Pang, Zhaowei Zhu, Na Di +4
Preference optimization methods such as DPO align large language models (LLMs) using paired comparisons, but their effectiveness can be highly sensitive to the quality and difficul…