RISED：代理多环境选择与自我蒸馏的评分标准

An LLM judge tags each rollout using a predefined rubric vocabulary shared across environments.

Across model backbones, RISED achieves the highest mean pass rate across environments and ranks first or second in every individual environment.

Abstract: Training a single LLM agent jointly across diverse interactive environments has attracted increasing attention as a route to generalist agents. Existing curriculum and data-selection strategies often allocate training at the environment level or prioritize local reward-based signals, without explicitly considering relationships between current rollouts across environments for prompt-gro…