Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards.

arXiv:2610.19868v1 Announce Type: new Abstract: Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification, both expensive to construct for stateful environments. Self-p