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清华等提出 One-Shot OPD：单条查询达全量数据 87% 增益

信息来源：X：面壁智能 OpenBMB (@OpenBMB)·
QwenLlama
原始标题：Post-training pipelines now use on-policy distillation (OPD) to hand a student the teacher's full next-token distribution at every prefix...

内容摘要

清华 NLP（OpenBMB 成员）联合中科院大学、东北大学、UIUC 和约翰霍普金斯大学提出 One-Shot OPD，将 OPD 训练集压缩到一条查询：数学任务上从 59.1 提升至 68.5（300 步），达到全量数据 OPD 69.8 的 87% 增益，并在代码、指令跟随和智能体工具使用上跨 Qwen、Llama、OLMo 成立。
内容分类AI 论文与研究
内容层级普通情报
发布时间（北京时间）
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信息来源X：面壁智能 OpenBMB (@OpenBMB)
站内情报编号intel-440c4e561f309adcdd578a77
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