most citedAgentic Reinforced Policy Optimization

4 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

ET-Agent: Incentivizing Effective Tool-Integrated Reasoning Agent via Behavior Calibration

Yifei Chen, Guanting Dong, Zhicheng Dou

Large Language Models (LLMs) can extend their parameter knowledge limits by adopting the Tool-Integrated Reasoning (TIR) paradigm. However, existing LLM-based agent training framew…

cs.AI2025

Toward Effective Tool-Integrated Reasoning via Self-Evolved Preference Learning

Yifei Chen, Guanting Dong, Zhicheng Dou

Tool-Integrated Reasoning (TIR) enables large language models (LLMs) to improve their internal reasoning ability by integrating external tools. However, models employing TIR often…

cs.AI2025

Revisiting RAG Ensemble: A Theoretical and Mechanistic Analysis of Multi-RAG System Collaboration

Yifei Chen, Guanting Dong, Yutao Zhu +1

Retrieval-Augmented Generation (RAG) technology has been widely applied in recent years. However, despite the emergence of various RAG frameworks, a single RAG framework still cann…

cs.LG20254 cited

Agentic Reinforced Policy Optimization

Guanting Dong, Hangyu Mao, Kai Ma +11

Large-scale reinforcement learning with verifiable rewards (RLVR) has demonstrated its effectiveness in harnessing the potential of large language models (LLMs) for single-turn rea…

cs.CL20254 cited

Tool-Star: Empowering LLM-Brained Multi-Tool Reasoner via Reinforcement Learning

Guanting Dong, Yifei Chen, Xiaoxi Li +7

Recently, large language models (LLMs) have shown remarkable reasoning capabilities via large-scale reinforcement learning (RL). However, leveraging the RL algorithm to empower eff…