ARISE: Adapting to Evolving Capability Gaps in Agentic Reinforcement Learning.

arXiv:2609.35532v1 Announce Type: new Abstract: As a long-horizon agent improves through experience, previously observed weaknesses may recede while new limitations emerge, continually changing what it still needs to learn. Yet the learning process often remai