Why RL Training Collapses on Long-Horizon Agents
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Been heads-down lately, but I finally had a couple of days to catch up on some recent papers. Sharing one of them here. Milestone-Guided Policy Learning for Long-Horizon Language Agents Zhejiang University (ZJU-REAL) · arXiv:2605.06078 · github.com/ZJU-REAL/BEACON It tackles a very concrete and fairly painful problem: when you train an agent on long tasks with RL, it doesn't just get a bit worse — it falls off a cliff as the horizon grows. TL;DR Trajectory-level RL (GRPO and friends) fails on…
1Key Takeaways
- Been heads-down lately, but I finally had a couple of days to catch up on some recent papers.
- TL;DR Trajectory-level RL (GRPO and friends) fails on….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that been heads-down lately, but I finally had a couple of days to catch up on some recent papers.
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