SOURCE-LINKED INTELLIGENCE
ActionSplice: In-Flight Action Editing for Interactive World Models
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 under the previous action, or trigger rollback that repeats completed evaluations. We introduce ActionSplice, an inference framework that formulates this problem as Counterfactual State Transport (CST). A lightweight corrector transports the interrupted backbone-native representation toward the matched state induced by the revised action at the same solver step. The worl
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T04:21:36.000Z
First collected: 2026-09-20T20:22:01.598Z. This is not the publication date.