English(EN) TecoPrompt: Temporal-Conservative Prompt Learning for Vision-Language Models

TecoPrompt 通过时序保守提示学习增强视觉-语言模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-16 04:00

研究人员开发了 TecoPrompt，一种用于视觉-语言模型鲁棒提示学习的新框架，在噪声监督下尤其有效。该方法从时序角度利用最优传输 (OT) 伪标签，通过检查多个 epoch 的轨迹稳定性来验证标签的可靠性。TecoPrompt 在各种数据集上取得了显著的性能提升，包括在具有大量噪声的 OxfordPets 数据集上准确率的显著提高。 AI

影响提高了视觉-语言模型对噪声数据的鲁棒性，有望在标签不完美的现实场景中得到更广泛的应用。

排序理由该条目是一篇研究论文，详细介绍了一种用于视觉-语言模型提示学习的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Zeyi Shao, Haowen Hua, Jiaxin Zhang, John See, Zeyd Boukhers, Cong Yang · 2026-09-16 04:00

TecoPrompt：面向视觉语言模型的时序保守提示学习

arXiv:2609.16858v1 Announce Type: new Abstract: Prompt learning adapts vision-language models, such as CLIP, by adjusting a small set of context tokens. However, under few-shot supervision, even moderate label noise can disrupt prompt optimization. To address this issue, we propo…

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TecoPrompt：面向视觉语言模型的时序保守提示学习

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