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RISED2 min read

RISED: Rubrics for Agentic Multi-Environment Selection and Self-Distillation

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…

By Apple ML Research
RISED: Rubrics for Agentic Multi-Environment Selection and Self-Distillation

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Originally published by Apple ML Research on Oct 6, 2026.

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