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Unlock 2x faster reinforcement learning by distilling group feedback into actionable language refinements that guide exploration.
Unlock SOTA performance in long-horizon search tasks with REDSearcher, a framework that slashes the cost of training by strategically synthesizing complex tasks and boosting core LLM capabilities *before* reinforcement learning.
VESPO stabilizes off-policy RL training for LLMs by directly reshaping sequence-level importance weights, tolerating 64x policy staleness and asynchronous execution without collapse.
