1 citations · 1 across the 9 of their papers we have counts for
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Cliff: Learning Process Rewards from the First Mistake
Peixuan Han, Runhui Wang, Ketan Ramaneti +3
Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for large language model (LLM) post-training, but its reliance on coarse outcome rewards le…
-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues
Peixuan Han, Hongyi Du, Jiayu Liu +3
Personalization is a crucial capability of modern language agents. However, current research primarily positions personalized agents as passive responders to user preferences, limi…
DRPG (Decompose, Retrieve, Plan, Generate): An Agentic Framework for Academic Rebuttal
Peixuan Han, Yingjie Yu, Jingjun Xu +1
Despite the growing adoption of large language models (LLMs) in scientific research workflows, automated support for academic rebuttal, a crucial step in academic communication and…
Self-Aligned Reward: Towards Effective and Efficient Reasoners
Peixuan Han, Adit Krishnan, Gerald Friedland +2
Reinforcement learning with verifiable rewards has significantly advanced reasoning in large language models (LLMs), but such signals remain coarse, offering only binary correctnes…