English(EN)ActionSplice: In-Flight Action Editing for Interactive World Models
新研究探索用于AI代理的高级世界模型
作者PulseAugur 编辑部·[4 个来源]·
研究人员正在为AI代理开发高级世界模型，重点是使它们能够理解和与动态环境进行交互。WorldAgen引入了一个用于统一状态-动作预测的框架，并进行测试时训练以适应新场景。PAN利用生成式潜在预测架构进行通用、可操作和长视界的世界模拟，旨在推动具身智能超越大型语言模型。ActionSplice提供了一个用于交互式世界模型的推理框架，允许在飞行中进行动作编辑，减少回滚的需要并提高效率。
AI
arXiv:2609.08162v1 Announce Type: new Abstract: How can vision-language-action (VLA) models adapt to new environments where world dynamics shift? While recent research has combined world modeling and action prediction to improve VLA performance, existing methods largely rely on p…
arXiv cs.AI
TIER_1English(EN)·PAN Team, Zihan Liu, Yi Gu, Mingkai Deng, Guangyi Liu, Zeyu Feng, Qiyue Gao, Yiyan Hu, Benhao Huang, Yichi Yang, Kun Zhou, Jiannan Xiang, Zhiting Hu, Zhengzhong Liu, Eric P. Xing·
arXiv:2511.09057v4 Announce Type: replace-cross Abstract: A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spontaneously or in response to their actions, and accordingly to plan and stra…
arXiv:2609.08230v1 Announce Type: cross Abstract: Chunk-autoregressive video world models typically condition each generated chunk on one action. An action received during sampling must therefore wait for the next chunk, condition future solver evaluations on a state produced und…
OpenWAM factorizes world-action pretraining into modular components to identify key design principles, yielding a scalable open model with strong simulation and real-robot performance.
