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LiveUpdated 2026-11-06 15:57 UTC

AutoRLBench

AutoRLBench is 🌐 Project. It is ranked #3335 on the AI Radar, in AI agents, first seen 13 days ago and shared in 2 posts (5.7k views).

Visit thinking-space.github.io

AutoRLBench — A benchmark for AI agents on real RL training runs A Benchmark for AI agents to diagnose and repair real RL training runs. Can an agent diagnose why a run fails — and repair it? Contribute a Run Browse Tasks Why this benchmark Most AI-for-AI evaluation is end-to-end: agents execute the full training pipeline and return only a final pass / fail result. This tells us whether it succeeds but not where it fails. AutoRLBench isolates RL training diagnosis and repair on real RL runs. 6 Failure Categories 14 Tasks actively collecting 2 Evaluation Levels Real failures are scarce — the ones that would make this benchmark matter are now…

What people said about AutoRLBench on X

✨ Introducing AutoRLBench — a benchmark built from real RL training failures. AI training AI is no longer hypothetical. Agents already run post-training, read the result, and decide what to do next. But a loop only turns if each round can be judged. When a run goes wrong, the agent has to find the root cause, and fix…

— @HBX_hbx, 13 days ago · 87 likes · see the post

AI 训练 AI 的关键不是能跑,是每一轮能不能被判断。跑歪了得找到根因再修,否则下一轮踩的还是坏信号。 AutoRLBench 用真实 RL 训练失败做任务:6 个失败类别、14 个任务,诊断题对隐藏 oracle,修复题改代码重跑看指标。榜单 v0.1 只出了诊断部分。

— @qingke_ai, 12 days ago · 5 likes · see the post

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FAQ

What is AutoRLBench?

🌐 Project It was first shared on X 13 days ago and is ranked #3335 on the AI Radar.

Is AutoRLBench free?

It is open source.

Who shared AutoRLBench?

2 accounts on X, including @HBX_hbx, @qingke_ai, in 2 posts totalling 5.7k views.

Every post is read and classified by AGK Intelligence: what it is, which market it belongs to, and whether the link is a real tool. 65.6k posts from 5k X accounts over the last 14 days, 10.4k tools, 19 markets. New posts are collected several times an hour and the full ranking is recomputed every hour — last update 2026-11-06 15:57 UTC. Full method.