Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments 事件

Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments arXiv:2606.05661v1 Announce Type: cross Abstract: Continual learning, the ability of AI systems to improve through sequential experience, has attracted substantial interest, but no high-quality benchmark exists to evaluate it. We introduce Continual Learning Bench (CL-Bench), the first difficult, expert-validated benchmark designed to measure whether LLM-based systems genuinely improve with experience.