English(EN) Real-Time Generation of Game Video Commentary with Multimodal LLMs: Pause-Aware Decoding Approaches

新的大语言模型方法可实现实时、考虑停顿的视频解说生成

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员开发了使用多模态大语言模型（MLLMs）生成实时视频解说的新方法。该研究提出了两种基于提示的解码策略：一种固定间隔方法和一种新颖的动态间隔方法，该方法根据话语时长调整预测时间。在日本和英语游戏数据集上的实验表明，动态间隔方法仅通过提示就能生成更符合人类时序和内容的解说。 AI

影响这项研究通过实现更自然、更及时的解说生成，有可能提高直播视频内容的易访问性和参与度。

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

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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arXiv cs.AI TIER_1 English(EN) · Anum Afzal, Yuki Saito, Hiroya Takamura, Katsuhito Sudoh, Shinnosuke Takamichi, Graham Neubig, Florian Matthes, Tatsuya Ishigaki · 2026-10-07 04:00

使用多模态大语言模型实时生成游戏视频解说：支持暂停的解码方法

arXiv:2603.02655v2 Announce Type: replace-cross Abstract: Real-time video commentary generation provides textual descriptions of ongoing events in videos. It supports accessibility and engagement in domains such as sports, esports, and livestreaming. Commentary generation involve…