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ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- ReflectRL framework learns from failed expert trajectories by having language models reflect on flaws before solving problems directly.
- 为何重要
- Matters for engineers training large language models on reasoning tasks who want to extract value from failed expert demonstrations.
- 注意
- Paper is recent preprint; practical overhead and scalability across production-scale models and datasets remain unvalidated.
收听本摘要
- language model
- reasoning
- post-train
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