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Trading Human Curation for Synthetic Augmentation in RLVR

Akshansh <last>, Leonardo Rosa Rodrigues, Michael Korostelev, Youssef Hassan, Mark E. Whiting
Jun 3, 2026 at 04:00
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arXiv:2606.03800v1 Announce Type: cross Abstract: The supply of high-quality training tasks is a central bottleneck for reinforcement learning from verifiable rewards (RLVR) on agentic language models. Each task requires a sandboxed setup, a prompt, and a hand-authored reward function, and only tasks that pass a quality bar produce useful...

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