English(EN) CanvasAnneal: Curriculum Reinforcement Learning for Diffusion Language Models

CanvasAnneal框架通过课程强化学习提升扩散语言模型的推理能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-14 04:00

研究人员开发了CanvasAnneal，一个用于扩散语言模型（DLMs）的新框架，该框架使用课程强化学习来提高它们的推理和工具使用能力。这种方法在训练的初始阶段注入来自更强教师模型的指导，并随着DLM学会独立生成推理轨迹而逐渐减少。在MATH500和Countdown等基准测试上的实验表明，CanvasAnneal可以加速奖励的提高，并优于标准的diffu-GRPO，尽管收益因任务而异。 AI

影响这项研究可能导致在复杂推理和工具使用任务中能力更强的扩散模型，从而可能缩小与自回归模型的差距。

排序理由该集群包含一篇详细介绍扩散语言模型新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍扩散语言模型新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.LG TIER_1 English(EN) · Blake Olson, Yuhang Song, Emmett McQuinn, Yuan Shangguan · 2026-09-14 04:00

CanvasAnneal：用于扩散语言模型的课程强化学习

arXiv:2609.13060v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) offer promising parallel generation capabilities but lag behind autoregressive models in complex reasoning and tool-use tasks. While Reinforcement Learning (RL) has recently been applied to enhance D…

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CanvasAnneal：用于扩散语言模型的课程强化学习

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