AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents 事件

AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents arXiv:2606.02461v1 Announce Type: cross Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future episodes. Continual learning expects an agent to accumulate reusable experience across a stream of tasks, improve over time, and avoid interference from irrelevant experiences. Unfortunately, existing benchmarks struggle