# HelloWorld：让视频世界模型中的角色实现社交互动

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-08-05 08:00
- AIHOT 分数：57
- AIHOT 链接：https://aihot.virxact.com/items/cmsgv6bqh004uroxz95votm36
- 原文链接：https://arxiv.org/abs/2608.05070

## AI 摘要

HelloWorld 是一个支持用户与视频世界内角色进行社交互动的视频世界模型。用户只需按一次按钮，即可让屏幕中的角色转向镜头、挥手、点头或说出简短问候。该模型通过自蒸馏流程微调视频生成模型，并引入无需训练模块调节 DiT 交叉注意力掩码，以时间定位角色响应。

## 正文

Despite the remarkable recent progress of video world models, social interaction between users and the characters within these worlds remains unsupported. To fill this gap, we present HelloWorld, a video world model that enables social interaction with in-world characters. With a single button press, users can prompt the on-screen character to respond toward the camera, e.g., turning to the viewer, waving, nodding, or speaking a short greeting. To make these interactions natural, we propose a self-distillation pipeline that finetunes the video generation model on data synthesized by itself. Each synthesized clip contains both social interactions and camera motion, allowing the model to learn camera-pose conditioning without degrading interaction quality. At inference, we further introduce a training-free module that determines when the interaction occurs. Upon a button press, it modulates the cross-attention masks of the DiT so that the interaction-related text prompt attends only to the frames within the press window, temporally localizing the character's response. We further build HelloWorldBench, a 400-sample benchmark with three social interaction metrics alongside three conventional metrics, for evaluation. Experiments demonstrate that HelloWorld surpasses a variety of baselines in interaction quality, while maintaining state-of-the-art picture aesthetics and camera-pose following. Project page: https://github.com/AlayaLab/HelloWorld