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cs.CL2026
Recovering Diversity Without Losing Alignment: A DPO Recipe for Post-Trained LLMs
Vinay Samuel, Yapei Chang, Mohit Iyyer
Many open-ended instructions have multiple valid answers that users can benefit from seeing, but post-training often narrows an LLM's output space toward a small set of canonical r…
cs.CL2026
Argument Collapse: LLMs Flatten Long-Form Public Debate
Yekyung Kim, Yapei Chang, Chau Minh Pham +1
As LLMs are increasingly used to draft publicfacing arguments, they may flatten public debate by repeatedly introducing the same polished, plausible arguments. We study argument co…
cs.CL2025
Semantically-Aware Rewards for Open-Ended R1 Training in Free-Form Generation
Zongxia Li, Yapei Chang, Yuhang Zhou +4
Evaluating open-ended long-form generation is challenging because it is hard to define what clearly separates good from bad outputs. Existing methods often miss key aspects like co…