Awesome-Autoregressive-Visual-Generation
This is a repo to track the latest autoregressive visual generation papers 🌟.
❗️❗️❗️In addition, I am also maintaining an open-source high-performance image tokenization framework XQ-GAN 🚀. This framework supports both state-of-the-art multi-scale residual quantization (VAR/Infinity) and regular vector quantizations (VQ-GAN variants).
Image Tokenizers
- Neural Discrete Representation Learning Paper, NeurIPS 2017
- Generating Diverse High-Fidelity Images with VQ-VAE-2 Paper, NeurIPS 2019
- Taming Transformers for High-Resolution Image Synthesis Paper, CVPR 2021
- Autoregressive Image Generation using Residual Quantization Paper, CVPR 2022
- * BEIT V2: Masked Image Modeling with Vector-Quantized Visual Tokenizers (for understanding) Paper, Arxiv 2022
- Vector-quantized Image Modeling with Improved VQGAN Paper, ICLR 2022
- MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation Paper, NeurIPS 2022
- * PeCo: Perceptual Codebook for BERT Pre-training of Vision Transformers (for understanding) Paper, AAAI 2023
- * All in Tokens: Unifying Output Space of Visual Tasks via Soft Token (for understanding) Paper, CVPR 2023
- Regularized Vector Quantization for Tokenized Image Synthesis Paper, CVPR 2023
- Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization Paper, CVPR 2023
- Not all image regionsmatter: Masked vector quantization for autoregressive image generation Paper, CVPR 2023
- Spae: Semantic pyramid autoencoder for multimodal generation with frozen llms Paper, NeurIPS 2023
- HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes Paper, TMLR 2024
- Finite Scalar Quantization: VQ-VAE Made Simple Paper, ICLR 2024
- Planting a seed of vision in large language model Paper, ICLR 2024
- Language model beats diffusion–tokenizer is key to visual generation Paper, ICLR 2024
- Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis Paper, CVPR 2024
- Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction Paper, NeurIPS 2024
- An Image is Worth 32 Tokens for Reconstruction and Generation Paper, NeurIPS 2024
- Image Understanding Makes for A Good Tokenizer for Image Generation Paper, NeurIPS 2024
- Scaling the Codebook Size of VQGAN to 100,000 with a Utilization Rate of 99% Paper, Arxiv 2024
- Quantised Global Autoencoder: A Holistic Approach to Representing Visual Data Paper, Arxiv 2024
- VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation Paper, ICLR 2025
- OPEN-MAGVIT2: AN OPEN-SOURCE PROJECT TOWARD DEMOCRATIZING AUTO-REGRESSIVE VISUAL GENERATION Paper, Arxiv 2024
- MaskBit: Embedding-free Image Generation via Bit Tokens Paper, TMLR 2024
- ImageFolder: Autoregressive Image Generation with Folded Tokens 🚀 Paper, ICLR 2025
- Cosmos Tokenizer: A suite of image and video neural tokenizers Website
- Adaptive Length Image Tokenization via Recurrent Allocation Paper, Arxiv 2024
- Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective Paper, Arxiv 2024
- MUSE-VL: Modeling Unified VLM through Semantic Discrete Encoding Paper, Arxiv 2024
- TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation Paper, Arxiv 2024
- XQ-GAN: An Open-source Image Tokenization Framework for Autoregressive Generation Paper, Arxiv 2024
- Image and Video Tokenization with Binary Spherical Quantization Paper, Arxiv 2024
- Taming Scalable Visual Tokenizer for Autoregressive Image Generation Paper, Arxiv 2024
- Language-Guided Image Tokenization for Generation Paper, Arxiv 2024
- Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation Paper, Arxiv 2024
- Scaling Image Tokenizers with Grouped Spherical Quantization Paper, Arxiv 2024
- Taming Scalable Visual Tokenizer for Autoregressive Image Generation Paper, Arxiv 2024
- Spectral Image Tokenizer Paper, Arxiv 2024
- Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens Paper, Arxiv 2024
- Learnings from Scaling Visual Tokenizers for Reconstruction and Generation Paper, Arxiv 2024
- Language-Guided Image Tokenization for Generation Paper, Arxiv 2024
- Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models Paper, Arxiv 2024
- One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression Paper, Arxiv 2024
- QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation Paper, Arxiv 2025
- FlexTok: Resampling Images into 1D Token Sequences of Flexible Length Paper, Arxiv 2025
- UniTok: A Unified Tokenizer for Visual Generation and Understanding Paper, Arxiv 2025
- NFIG: Autoregressive Image Generation with Next-Frequency Prediction Paper, Arxiv 2025
- V2Flow: Unifying Visual Tokenization and Large Language Model Vocabularies for Autoregressive Image Generation Paper, Arxiv 2025
- “Principal Components” Enable A New Language of Images Paper, Arxiv 2025
- Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the-Art Image Tokenization Paper, Arxiv 2025
- Tokenize Image as a Set Paper, Arxiv 2025
- D2C: Unlocking the Potential of Continuous Autoregressive Image Generation with Discrete Tokens, Paper, Arxiv 2025
- Robust Latent Matters: Boosting Autoregressive Image Generation with Sampling Error Synthesis Paper, Arxiv 2025
- Bridging Continuous and Discrete Tokens for Autoregressive Visual Generation Paper, Arxiv 2025
- MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization Paper, Arxiv 2025
- GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image Generation Paper, Arxiv 2025
- MedITok: A Unified Tokenizer for Medical Image Synthesis and Interpretation Paper, Arxiv 2025
AutoRegressive Image Generation
- Conditional image generation with pixelcnn decoders Paper, NeurIPS 2016
- DiVAE : Photorealistic Images Synthesis with Denoising Diffusion Decoder Paper
- Vector Quantized Diffusion Model for Text-to-Image Synthesis Paper
- MaskGIT: Masked Generative Image Transformer Paper
- BEIT: BERT Pre-Training of Image Transformers Paper
- BEIT V2: Masked Image Modeling with Vector-Quantized Visual Tokenizers Paper
- MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis Paper
- Sequential modeling enables scalable learning for large vision models Paper, Arxiv 2023
- 4m: Massively multimodal masked modeling Paper, NeurIPS 2023
- Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation Paper, Arxiv 2024
- ControlVAR: Exploring Controllable Visual Autoregressive Modeling Paper, Arxiv 2024
- Autoregressive Image Generation without Vector Quantization Paper, Arxiv 2024
- MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis Paper, Arxiv 2024
- ANOLE: AnOpen,Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation Paper, Arxiv 2024
- VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling Paper, Arxiv 24
- Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining Paper, Arxiv 24
- Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model Paper, Arxiv 2024
- Scalable Autoregressive Image Generation with Mamba Paper, Arxiv 2024
- SHOW-O: ONE SINGLE TRANSFORMER TO UNIFY MULTIMODAL UNDERSTANDING AND GENERATION Paper, ICLR 2025
- DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation Paper, Arxiv 2024
- Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens Paper, Arxiv 2024
- Customize Your Visual Autoregressive Recipe with Set Autoregressive Modeling Paper, Arxiv 2024
- M-VAR: Decoupled Scale-wise Autoregressive Modeling for High-Quality Image Generation Paper, Arxiv 2024
- MMAR:TowardsLossless Multi-Modal Auto-Regressive Probabilistic Modeling Paper, Arxiv 2024
- Randomized Autoregressive Visual Generation Paper, Arxiv 2024
- Elucidating the design space of language models for image generation Paper, Arxiv 2024
- Toward Guidance-Free AR Visual Generation via Condition Contrastive Alignment Paper, ICLR 2025
- CART: Compositional Auto-Regressive Transformer for Image Generation Paper, Arxiv 2024
- CoDe: Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Paper, Arxiv 2024
- X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Paper, Arxiv 2024
- JetFormer: An Autoregressive Generative Model of Raw Images and Text Paper, Arxiv 2024
- Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis Paper, Arxiv 2024
- Liquid: Language Models are Scalable Multi-modal Generators Paper, Arxiv 2024
- RandAR: Decoder-only Autoregressive Visual Generation in Random Orders Paper, Arxiv 2024
- FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching Paper, Arxiv 2024
- Parallelized Autoregressive Visual Generation Paper, Arxiv 2024
- Next Patch Prediction for Autoregressive Visual Generation Paper, Arxiv 2024
- MetaMorph: Multimodal Understanding and Generation via Instruction Tuning Paper, Arxiv 2024
- VARGPT: Unified Understanding and Generation in a Visual Autoregressive Multimodal Large Language Model Paper, Arxiv 2024
- Can We Generate Images with CoT? Let’s Verify and Reinforce Image Generation Step by Step Paper, Arxiv 2024
- Generative Autoregressive Transformers for Model-Agnostic Federated MRI Reconstruction Paper, Arxiv 2025
- Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling Paper, Arxiv 2025
- VARGPT: Unified Understanding and Generation in a Visual Autoregressive Multimodal Large Language Model Paper, Arxiv 2025
- Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation Paper, Arxiv 2025
- Autoregressive Image Generation Guided by Chains of Thought Paper, Arxiv 2025
- Fractal Generative Models Paper, Arxiv 2025
- FlexVAR: Flexible Visual Autoregressive Modeling without Residual Prediction Paper, Arxiv 2025
- Direction-Aware Diagonal Autoregressive Image Generation Paper, Arxiv 2025
- DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies Paper, Arxiv 2025
- Unified Autoregressive Visual Generation and Understanding with Continuous Tokens Paper, Arxiv 2025
- Autoregressive Image Generation with Randomized Parallel Decoding Paper, Arxiv 2025
- Neighboring Autoregressive Modeling for Efficient Visual Generation Paper, Arxiv 2025
- Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models Paper, Arxiv 2025
- Harmonizing Visual Representations for Unified Multimodal Understanding and GenerationPaper, Arxiv 2025
- FastVAR: Linear Visual Autoregressive Modeling via Cached Token Pruning Paper, Arxiv 2025
- Training-Free Text-Guided Image Editing with Visual Autoregressive Model Paper, Arxiv 2025
- Transfer between Modalities with MetaQueries Paper, Arxiv 2025
- PixelFlow: Pixel-Space Generative Models with Flow, Paper, Arxiv 2025
- Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models Paper, Arxiv 2025
- LazyMAR: Accelerating Masked Autoregressive Models via Feature Caching Paper, Arxiv 2025
- Fast Autoregressive Models for Continuous Latent Generation Paper, Arxiv 2025
- X-Fusion: Introducing New Modality to Frozen Large Language Models Paper, Arxiv 2025
- T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT Paper, Arxiv 2025
- Continuous Visual Autoregressive Generation via Score Maximization Paper, ICML 2025
- DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail Prediction Paper, Arxiv 2025
- BLIP3-o: A Family of Fully Open Unified Multimodal Models—Architecture, Training and Dataset Paper, Arxiv 2025
- DiSA: Diffusion Step Annealing in Autoregressive Image Generation Paper, Arixv 2025
- StyleAR: Customizing Multimodal Autoregressive Model for Style-Aligned Text-to-Image Generation Paper, Arxiv 2025
- TensorAR: Refinement is All You Need in Autoregressive Image Generation Paper, Arxiv 2025
- D-AR: Diffusion via Autoregressive Models Paper, Arxiv 2025