From the 1 of 11 linked papers with an AI index.
11 papers
ReDiPPO: Reference-Guided Value Calibration and Discrepancy-Aware Token Reweighting for Mathematical Reasoning
Zhenrong Zhang, Fei Wu, Jun Du +2
The paper presents ReDiPPO, a PPO-based reinforcement learning framework that leverages reference answers to guide value estimation and reweights token-level advantages based on di…
EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via Action Pruning
Jiawei Liu, Qisi Chen, Jianshu Zhang +2
Large Language Models (LLMs) excel at complex reasoning through search algorithms, yet current strategies often suffer from massive token consumption due to redundant exploration o…
PEARL: Training Socratic Tutors with Pedagogically Aligned Reinforcement Learning
Qikai Chang, Zhenrong Zhang, Linbo Chen +4
Large Language Models (LLMs) have shown promise as educational tutors, yet effective tutoring requires more than solving problems: it must provide progressive Socratic guidance and…
THOR: Tool-Integrated Hierarchical Optimization via RL for Mathematical Reasoning
Qikai Chang, Zhenrong Zhang, Pengfei Hu +6
Large Language Models (LLMs) have made remarkable progress in mathematical reasoning, but still continue to struggle with high-precision tasks like numerical computation and formal…
Step Potential Advantage Estimation: Harnessing Intermediate Confidence and Correctness for Efficient Mathematical Reasoning
Fei Wu, Zhenrong Zhang, Qikai Chang +3
Reinforcement Learning with Verifiable Rewards (RLVR) elicits long chain-of-thought reasoning in large language models (LLMs), but outcome-based rewards lead to coarse-grained adva…
See then Tell: Enhancing Key Information Extraction with Vision Grounding
Shuhang Liu, Zhenrong Zhang, Pengfei Hu +5
In the digital era, the ability to understand visually rich documents that integrate text, complex layouts, and imagery is critical. Traditional Key Information Extraction (KIE) me…