Skip to content
Hot eventLive

EESD:编码智能体自纠正的适应性证据自蒸馏

1 reports1 sources3 hr ago updated

Get the story

AI overview

2026年10月7日,arXiv Software Engineering 频道发布一手论文,提出 Effective-Evidence Self-Distillation(EESD),探讨编程智能体自纠正应承载多少证据。该方法将执行反馈中的转移支持与证据质量分开建模,利用 Dirichlet 后验生成带不确定性惩罚的权重,并以此进行 KL 锚定的纠正学习。目前报道仅涉及该论文的方法框架,未披露实验数据、代码或后续验证进展。

Generated from reports · updated 3 hr ago

Timeline

Follow the coverage from different angles.

Oct 7, 2026
  1. arXiv · Software Engineering
    编程智能体的自纠正应承载多少证据?面向自蒸馏的自适应 Dirichlet 证据

    论文提出 Effective-Evidence Self-Distillation(EESD),把执行反馈中的转移支持与证据质量分开建模,用 Dirichlet 后验生成带不确定性惩罚的权重进行 KL 锚定的纠正学习。

Heat trend

Current heat 9·Comparable peak 10(Oct 7)·Comparable change over 24 hours –

02.557.510Oct7Oct7Oct7Oct7

The trend compares only the same participants observed continuously; its range may be smaller than the current heat count. Move or click on the chart to inspect hourly heat; use the left and right arrow keys to switch.