Self Gradient Forcing: Native Long Video Extrapolation
Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-truth video contexts. This reduces exposure bias, but the historical key-value cache is still used by future frames only as frozen rollout state. As a result, future losses cannot supervise how earlier generated latents should be written into more useful keys and values for later video-latent generation. We call this the
Record details
Published: 21 July 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Bias & fairness · Children & education
Retrieved: 23 July 2026
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ethics.ai (21 July 2026), “Self Gradient Forcing: Native Long Video Extrapolation,” evidence record 12651, https://ethics.ai/record/12651 (originally published by HuggingFace Daily Papers).
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