SSD: Spatially Speculative Decoding Accelerates Autoregressive Image Generation

arXiv:2606.20543 · cs.CV · Submitted 2026-06-18 · Read on arXiv

cs.CV

Submitted: 2026-06-18

Updated: 2026-09-27

Project page: https://shilongxiang.github.io/SSD/Abstract

Terminology

• Verification — 63× in this paper · explained in 2 episodes
• Speculative Decoding — 23× in this paper · explained in 2 episodes
• Spatially Speculative Decoding — 10× in this paper
• Transformer — 10× in this paper · explained in 2 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• KV cache — 2× in this paper · explained in 3 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Prompt Adherence — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-distillation — 1× in this paper · explained in 6 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Accelerating Large Language Model Decoding with Speculative Sampling
• Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
• Distilling the Knowledge in a Neural Network
• Classifier-Free Diffusion Guidance
• ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
• GPT-4o System Card
• Annealed Relaxation of Speculative Decoding for Faster Autoregressive Image Generation
• EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
• DeepSeek-V3 Technical Report
• Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining
• L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models
• Multi-Scale Local Speculative Decoding for Image Generation
• Searching for Activation Functions
• GLU Variants Improve Transformer
• Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
• Chameleon: Mixed-Modal Early-Fusion Foundation Models
• Emu3: Next-Token Prediction is All You Need
• Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
• Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation
• FlashAR: Efficient Post-Training Acceleration for Autoregressive Image Generation

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