English(EN) Harness-Aware Distillation for Small Language Model Agents

新的蒸馏方法改进了小型语言模型代理

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-05 04:00

研究人员开发了一种名为 Harness 感知蒸馏 (HAD) 的新方法，以改进小型语言模型代理的训练。该技术侧重于教会学生模型教师模型在其周围的 Harness 之外所添加的内容，而不是模仿教师的完整输出。HAD 包含一个动作偏好机制和一个有效性检查来指导学生，使其能够在不需要任务奖励或成功标签的情况下更有效地从 Harness 信息中学习。在长视野代理基准测试上的实验表明，HAD 的性能优于标准的 On-policy 蒸馏方法，能够减少无效循环并更好地恢复错误。 AI

影响这项新的蒸馏技术可以实现更高效的训练，从而为复杂任务培养更小、更有能力的 AI 代理。

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arXiv cs.AI TIER_1 English(EN) · Moonseok Choi, Taehong Moon, Giung Nam, Juho Lee · 2026-10-05 04:00

面向小语言模型智能体的约束感知蒸馏

arXiv:2610.02858v1 Announce Type: new Abstract: Language model agents are deployed with a harness, the software around the model that manages its context, tools, and feedback. When such an agent is distilled into a smaller one, the harness stays in place, so the student mainly ne…

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面向小语言模型智能体的约束感知蒸馏

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