Papers by Congmin Zheng

2 papers
Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning (2025.findings-acl)

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Challenge: Large language models (LLMs) have advanced mathematical reasoning, but they still struggle with out-of-distribution (OOD) issues.
Approach: They propose a framework to evaluate the logical validity of reasoning steps . they retrieves semantically similar questions and steps for PRM as a warmup .
Outcome: The proposed framework outperforms baseline models on multiple real-world datasets.
A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage (2026.acl-long)

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Challenge: Large Language Models (LLMs) have advanced reasoning ability, yet conventional alignment remains dominated by outcome reward models that judge only final answers.
Approach: They summarize applications across math, code, text, multimodal reasoning, robotics, and agents . goal is to clarify design spaces, reveal open challenges, and guide future research toward fine-grained, robust reasoning alignment.
Outcome: The proposed model enables finer credit assignment, richer diagnostics, and improved robustness.

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