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SGF+: Decoupling Gradient Flows for Autoregressive Video Generation

Paper recorded by Signals 4 on 2026-10-07 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-07 on arXiv · recorded by Signals 4 on 2026-10-08

Category: cs.CV · 计算机视觉 · first seen 2026-10-08

Abstract

Autoregressive video generation requires denoising the current frames while writing their key-value representations as context for future predictions. However, these two roles typically share parameters, and we find that their gradients exhibit distinct patterns and systematic negative alignment, hindering the joint optimization of visual quality and temporal consistency. We introduce Self Gradien

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#328 most recent of 756 cs.CV papers we have recorded · ↑ newer: Detecting Adversarial Images through Response Profiles of Vision-Langu · ↓ older: GraphRectify: Graph-Based Transfer of Adversarial Example Detectors Ac
Cite this page: SGF+: Decoupling Gradient Flows for Autoregressive Video Generation: the #328 most recent of 756 cs.CV papers we have recorded (as of 2026-10-07). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/sgf-decoupling-gradient-flows-for-autoregressive-video-generation.html
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