Author

Zhan Su

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#natural language process... May 2026

STOP: Structured On-Policy Pruning of Long-Form Reasoning in Low-Data Regimes

STOP (Structured On-policy Pruning), an on-policy algorithm for analyzing and pruning long-form reasoning traces, which improves the structural efficiency of generated reasoning, and reallocates reasoning effort away from redundant verification and backtracking toward more productive exploration.

Chenjun Xu, Zhen-Nan Zhou, Zhan Su et al. · arXiv.org · 0 citations

Jul 2026

Search-on-Graph-R1: Training Large Language Models to Search Knowledge Graphs with Reinforcement Learning

Search-on-Graph-R1 (\sogrone{}), which internalizes this navigation into a compact 8B model through supervised fine-tuning (SFT) followed by reinforcement learning (RL), which surpasses every frozen frontier-LLM system in their comparison and posts the strongest results on CWQ of any system the authors compare against.

J. Sun, Hao Yu, Fengran Mo et al. · arXiv.org · 1 citation · ⚡1

Jul 2026

TAPO: Transition-Aware Policy Optimization for LLM Agents

This work proposes TAPO: Transition-Aware Policy Optimization for LLM Agents, a unified training framework that alternates between policy optimization and transition supervision, and demonstrates that TAPO consistently improves task performance over pure policy optimization baselines.

Cong Li, Pei-Xi Peng, Yisen Zhao et al. · arXiv.org · 1 citation