Next Forcing: Causal World Modeling with Multi-Chunk Prediction

Autoregressive video generation has emerged as a powerful paradigm for World Action Models (WAMs). However, existing approaches suffer from slow training convergence and limited converged accuracy, particularly at high frame rates, as the training supervision is confined to the current chunk without explicit signals about future dynamics; they also suffer from slow inference due to iterative video denoising.

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• llms
• agents
• diffusion
• benchmarks