ProAS reshapes advantages for multi-turn agent reinforcement learning
On Qwen2.5 instruct models, reported peaks reach 94.3% on ALFWorld and 70.8% on WebShop.
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AI model
Qwen2.5-1.5B-Instruct
- Mentions · 7d1
- Mentions · 30d2
- All mentions2
- First seenOct 13, 2026
- Last mentioned6d ago
Timeline
2 articles · newest firstSERO: Learning from Executable Oracle Continuations for Long-Horizon Agentic Reinforcement Learning
SERO trains long-horizon agents using executable oracle continuations and reachability weighting on ALFWorld and WebShop.
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Appears with
- Qwen2.5-7B-Instructai model · 2
- WebShopproduct · 1
- ALFWorldproduct · 1
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