OpenForgeRL: Train Harness-native Agents in Any Environment
Score
81提出全新训练范式，首次实现复杂推理框架智能体的端到端RL训练，并揭示harness与RL交互规律，信息增量高。
实验覆盖多个基准与harness，结果详实且分析深入，论文结构严谨，质量上乘。
开源框架可直接复现使用，降低训练门槛，但错误恢复等关键能力仍未解决，实用价值较高。
论文于2026年7月发布，紧跟AI Agent与RL前沿，时效性极强。
arXiv预印本且来自AI/CL/LG领域，暂无同行评审，但方法公开且可复现，信源可信。
Base 89.5 × T2 Source weight ×0.9 = 81
Curation line 70Selected
Why selected
The paper proposes an innovative training paradigm with validated practicality, and the open-source framework has high reusability, though key capabilities like error recovery see limited improvement; overall quality is excellent.
AI commentary
「This paper is a must-read for AI agent engineers and researchers stuck with complex inference harnesses that hinder end-to-end training. OpenForgeRL finally bridges the gap between harnesses and RL, letting SFT/RL stacks natively use production-grade inference frameworks. Note that error recovery remains unsolved, but now there's a reproducible playground. For teams deploying reliable GUI or tool agents, this framework is essential.」
Quick overview
OpenForgeRL introduces a lightweight proxy and Kubernetes orchestrator that converts model calls from complex inference harnesses (e.g., Claude Code, Codex) into trainable RL data, enabling end-to-end training. On tool-based and multimodal GUI tasks, it matches or surpasses larger models with only hundreds to thousands of samples, and provides analysis on how harness choice and RL shape agent behavior, revealing improvements in self-verification and multi-step planning while error recovery remains weak.
- OpenForgeRL decouples training from inference via a proxy and K8s orchestrator, enabling end-to-end training on any harness and environment.
- Achieves 31.7 pass^3, 33.7, 37.7 on ClawEval, QwenClawBench, OSWorld-Verified, outperforming open baselines of similar size.
- RL improves agent reliability (self-verification, tool coverage, multi-step plans) but error recovery remains weak.
- Requires only hundreds to thousands of tasks for significant performance gains.
Full text
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