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这项由新加坡国立大学LV-NUS实验室联合复旦大学、北京大学与字节跳动公司共同开展的研究，于2026年6月发布于arXiv预印本平台，论文编号为arXiv:2606.17628v1。研究的核心成果是一个名为OPD-Evolver的智能体训练框架，它让一个参数量仅90亿的小模型在多项测试中追平甚至超越了参数量高达3970亿的超大模型。