Harness Scaling Trains Agentic RL Across Diverse Configs for Better Generalization
RUC · hf · 2026-10-22
Researchers from Renmin University propose Harness Scaling, a new scaling dimension for agentic RL that trains across diverse execution configurations instead of a single fixed harness, boosting generalization to unseen harnesses for tool use, context management, and long-horizon interaction.
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