English(EN) IPS: In-Prompt Process Supervision for Short Video Content Moderation

新的提示内过程监督框架增强了用于视频审核的MLLMs

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

研究人员开发了一个名为IPS（In-Prompt Process Supervision，提示内过程监督）的新框架，以提高多模态大型语言模型（MLLMs）在短视频内容审核方面的准确性。该方法在微调过程中引入了对辅助问题的顺序推理，使MLLMs能够更好地关注特定策略的细节。IPS在各种基准测试中表现优于基线MLLMs，并通过有效利用模型生成的注释且性能损失最小而显示出可扩展性。 AI

影响提高了使用LLMs的内容审核系统的准确性，可能导致在工业环境中实现更具可扩展性和鲁棒性的审核。

排序理由这是一篇详细介绍多模态大型语言模型新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 这是一篇详细介绍多模态大型语言模型新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Mingchao Liu, Yu Sun, Ruixiao Sun, Xin Dong, Xiang Shen, Hongwei Wang, Hongyu Xiong, Yang Song · 2026-05-05 04:00

IPS：用于短视频内容审核的提示内过程监督

arXiv:2412.15251v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are effective at capturing the semantics of short video content; however, they often fail to attend to the policy-specific details required for reliable content moderation. To address thi…

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报道来源 [1]

IPS：用于短视频内容审核的提示内过程监督

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