Author
University of Chinese Academy of Sciences
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This work introduces ScaleCUA, a unified framework that scales online RL for CUAs via verifiable task synthesis and efficient training, and designs VeriGen, an end-to-end framework for generating verifiable RL tasks through iterative docker interactions and a multi-agent feedback loop.
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