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Junxiao Liu

2 accepted papers

2025

Process-based Self-Rewarding Language Models

ACL 2025finding

Large Language Models have demonstrated outstanding performance across various downstream tasks and have been widely applied in multiple scenarios. Human-annotated preference data is used for training to further improve LLMs’ performance, which is constrained by the upper limit of human performance.…

2025

R-PRM: Reasoning-Driven Process Reward Modeling

EMNLP 2025

Process Reward Models (PRMs) have emerged as a promising solution to address the reasoning mistakes of large language models (LLMs). However, existing PRMs typically output evaluation scores directly, limiting both learning efficiency and evaluation accuracy. This limitation is further compounded by