ZipAR: Parallel Autoregressive Image Generation through Spatial Locality
Yefei He, Feng Chen, Yuanyu He, Shaoxuan He, Hong Zhou, Kaipeng Zhang, Bohan Zhuang
2025Year
6Top-tier citations
Abstract
In this paper, we propose ZipAR, a training-free, plug-and-play parallel decoding framework for accelerating autoregressive (AR) visual generation. The motivation stems from the observation that images exhibit local structures, and spatially distant regions tend to have minimal interdependence. Given a partially decoded set of visual tokens, in addition to the original next-token prediction scheme in the row dimension, the tokens
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Cited by top-tier papers6
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- Multi-Scale Local Speculative Decoding for Image GenerationElia Peruzzo, Guillaume Sautiere, Amir HabibianCVPR 2026 · 3 citations
- A Flat Vocabulary or a Rich Hierarchy? Re-introducing Intrinsic Structure Transforms the Autoregressive Image GenerationLixuan He, Shikang ZhengICML 2026
- Annealed Relaxation of Speculative Decoding for Faster Autoregressive Image GenerationXingyao Li, Fengzhuo Zhang, Cunxiao Du, Hui JiAAAI 2026
Builds on13
- Swin Transformer: Hierarchical Vision Transformer using Shifted WindowsZe Liu, Yutong Lin, Yue Cao, Han Hu et al.ICCV 2021 · 31,683 citations
- Diffusion Models Beat GANs on Image SynthesisPrafulla Dhariwal, Alexander Quinn NicholNeurIPS 2021 · 13,211 citations
- Fast Inference from Transformers via Speculative DecodingYaniv Leviathan, Matan Kalman, Yossi MatiasICML 2023 · 1,472 citations
- ImageReward: Learning and Evaluating Human Preferences for Text-to-Image GenerationJiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong et al.NeurIPS 2023 · 1,310 citations
- Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale PredictionKeyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng et al.NeurIPS 2024 · 1,199 citations
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