ReWorld: An Interactive World Model with Long-Horizon Memory· 具有长时记忆的交互式世界模型
An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control wants a short horizon, memory wants an unbounded one. ReWorld separates the two during training and bounds them at inference. Mixed per-head attention windows confine most heads to the recent past while a small set of global heads attends over the entire history, and random head routing keeps either capability from binding to particular heads; random chunk dropping makes sparse histories in-distribution. At inference the whole past lives under a fixed budget: a bounded KV cache backed by a pose-indexed landmark bank, from which the model retrieves the landmarks nearest the current pose. A metric-scale-aligned data engine places eight sourc
通过模型分离控制和记忆,实现长时记忆的交互式世界模型。
- 核心方法
- 使用混合注意力窗口在训练时分开控制和记忆,通过随机头路由保持灵活性,随机块丢弃确保稀疏历史在分布内,推理时采用固定预算的KV缓存和姿态索引的地标银行。
- 适合谁读
- 研究者 / 工程师
- 要解决的问题
- 如何构建一个既能实时响应用户操作,又能有效记忆历史状态的交互式世界模型。
- 关键实验
- 未提供
- 主要贡献
- 提出了一种新颖的交互式世界模型架构,实现了长时记忆与实时控制的平衡。
- 意义与局限
- 为构建更复杂、更自然的交互系统提供了理论基础和技术支持,但可能在实际部署中面临效率和资源挑战。