arXiv 2610.22347 · cs.CV · 2026-10-15
Speculative Forcing for Efficient Autoregressive Video Generation
Hyunwook Choi, Seungryong Kim, Dongyoon Han, Sangdoo Yun
NAVER AI Lab
在最新榜 #159 本站收录于 2026-10-21
一句话要点
推测式强制把中间去噪结果当草稿，提前接受已收敛的 token，加速自回归视频生成。
Speculative Forcing treats intermediate estimates as drafts and accepts converged tokens early to speed up autoregressive video generation.
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主题与学科
同主题：视觉生成
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- Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation ▲364
- DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models ▲325
- UltraText Bench: A Comprehensive Bilingual Benchmark for Evaluating Visual Text Rendering in Image Generation ▲197
- Matrix-Game 4.0: Harnessing Video Models for Real-Time Playable Game Worlds ▲182
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-22。
要点由本站根据摘要自写，不转载摘要原文，请阅读原文。