Next Forcing: Causal World Modeling with Multi-Chunk Prediction
- Published
- Source
- arXiv
- Paper number
- 383
- Field
- Computer Vision
- arXiv ID
- 2606.11187
Key points
- We solve the myopic supervision problem in autoregressive video generation with multi-chunk prediction (MCP).
- A causal MCP chain lets near-future predictions inform far-future predictions and provides dense supervision to the main model.
- We achieve SOTA on RoboTwin, with 94.1% on Clean and 93.5% on Random.
- At 50 fps, it delivers a 93.1% relative improvement over LingBot-VA and a 2.3x training speedup.
- General video pretraining also reduces FVD by more than 50%, demonstrating generality beyond robot-specific data.
- Keeping the MCP module at inference time doubles inference speed while preserving accuracy.
Paper links
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