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cs.CV2026
Annealed Relaxation of Speculative Decoding for Faster Autoregressive Image Generation
Xingyao Li, Fengzhuo Zhang, Cunxiao Du +1
Despite significant progress in autoregressive image generation, inference remains slow due to the sequential nature of AR models and the ambiguity of image tokens, even when using…
cs.CV2025
Sparse-to-Dense: A Free Lunch for Lossless Acceleration of Video Understanding in LLMs
Xuan Zhang, Cunxiao Du, Sicheng Yu +4
Due to the auto-regressive nature of current video large language models (Video-LLMs), the inference latency increases as the input sequence length grows, posing challenges for the…
cs.CV2025
Error Analyses of Auto-Regressive Video Diffusion Models: A Unified Framework
Jing Wang, Fengzhuo Zhang, Xiaoli Li +5
Auto-Regressive Video Diffusion Models (AR-VDMs) have shown strong capabilities in generating long, photorealistic videos, but suffer from two key limitations: (i) history forgetti…