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README.md

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-license: apache-2.0
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+# Official Repo of Reagent.
+Paper:
+
+## Abstract:
+Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use.
+However, most methods still relies on sparse outcome-based reward for training.
+Such feedback fails to differentiate intermediate reasoning quality, leading to suboptimal training results.
+In this paper, we introduce \textbf{Agent Reasoning Reward Model (Agent-RRM)}, a multi-faceted reward model that produces structured feedback for agentic trajectories, including (1) an explicit reasoning trace , (2) a focused critique that provides refinement guidance by highlighting reasoning flaws, and (3) an overall score that evaluates process performance.
+Leveraging these signals, we systematically investigate three integration strategies: \textbf{Reagent-C} (text-augmented refinement), \textbf{Reagent-R} (reward-augmented guidance), and \textbf{Reagent-U} (unified feedback integration).
+Extensive evaluations across 12 diverse benchmarks demonstrate that Reagent-U yields substantial performance leaps, achieving 43.7\% on GAIA and 46.2\% on WebWalkerQA, validating the effectiveness of our reasoning reward model and training schemes.
+
+## GitHub Repository
+The official codebase, including training and evaluation scripts for Reagent, can be found on the project's GitHub repository: https://github.com/kxfan2002/Reagent
+
+## Citation
+
+```bash
+
+```
+---
+license: apache-2.0
+---