mlsanityData to 7 Oct 2026

aMUSEd: An Open MUSE Reproduction

arXiv 2401.01808 ↗First posted 3 Jan 2024cs.CVcited by 32

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

We present aMUSEd, an open-source, lightweight masked image model (MIM) for text-to-image generation based on MUSE. With 10 percent of MUSE's parameters, aMUSEd is focused on fast image generation. We believe MIM is under-explored compared to latent diffusion, the prevailing approach for text-to-image generation. Compared to latent diffusion, MIM requires fewer inference steps and is more interpretable. Additionally, MIM can be fine-tuned to learn additional styles with only a single image. We hope to encourage further exploration of MIM by demonstrating its effectiveness on large-scale text-to-image generation and releasing reproducible training code. We also release checkpoints for two models which directly produce images at 256x256 and 512x512 resolutions.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 32 of its 41 references that are in the map. First posted on arXiv 3 Jan 2024.

Builds on

32 of 41 references.

Closest ancestors · 1

Same direction, newest first

  1. 2022Hierarchical Text-Conditional Image Generation with CLIP Latents13 Apr

Other references · 31

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  6. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  7. 2020Denoising Diffusion Implicit Modelscited by 9,655
  8. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  9. 2022Scalable Diffusion Models with Transformerscited by 5,931
  10. 2017On Calibration of Modern Neural Networkscited by 4,860
  11. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  12. 2021Zero-Shot Text-to-Image Generationcited by 4,276
19 more
  1. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  2. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  3. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  4. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  5. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,286
  6. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,961
  7. 2018Hierarchical Neural Story Generationcited by 1,182
  8. 2019An Introduction to Variational Autoencoderscited by 997
  9. 2022DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Modelscited by 924
  10. 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 854
  11. 2023Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inferencecited by 826
  12. 2023Language Is Not All You Need: Aligning Perception with Language Modelscited by 543
  13. 2022Fast Sampling of Diffusion Models with Exponential Integratorcited by 526
  14. 2023UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Modelscited by 441
  15. 2020How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answeringcited by 439
  16. 2023DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Modelscited by 431
  17. 2023LCM-LoRA: A Universal Stable-Diffusion Acceleration Modulecited by 211
  18. 2023DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statisticscited by 161
  19. 2022CM3: A Causal Masked Multimodal Model of the Internetcited by 142

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 15; 2025: 14; 2026: 3.

32 papers.

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  1. 2024World Model on Million-Length Video And Language With Blockwise RingAttentioncited by 196
  2. 2024iVideoGPT: Interactive VideoGPTs are Scalable World Modelscited by 136
  3. 2025MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraftcited by 93
  4. 2024WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokenscited by 87
  5. 2025Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understandingcited by 83
  6. 2025A Survey on Diffusion Language Modelscited by 75
  7. 2024Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directionscited by 39
  8. 2024VidTok: A Versatile and Open-Source Video Tokenizercited by 35
  9. 2025Halton Scheduler For Masked Generative Image Transformercited by 30
  10. 2024HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editingcited by 29
  11. 2024Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local Similaritiescited by 27
  12. 2024Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Surveycited by 27
20 more
  1. 2025EditMGT: Unleashing Potentials of Masked Generative Transformers in Image Editingcited by 12
  2. 2025Stay-Positive: A Case for Ignoring Real Image Features in Fake Image Detectioncited by 11
  3. 2024Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitatorscited by 9
  4. 2025Fast Autoregressive Video Generation with Diagonal Decodingcited by 8
  5. 2024Generating Coherent Sequences of Visual Illustrations for Real-World Manual Taskscited by 6
  6. 2025Dimathtt[M]O: Distilling Masked Diffusion Models into One-step Generatorcited by 5
  7. 2025NEP: Autoregressive Image Editing via Next Editing Token Predictioncited by 5
  8. 2025Soft-Di[M]O: Improving One-Step Discrete Image Generation with Soft Embeddingscited by 5
  9. 2024TMT: Tri-Modal Translation between Speech, Image, and Text by Processing Different Modalities as Different Languagescited by 4
  10. 2025Training Data Provenance Verification: Did Your Model Use Synthetic Data from My Generative Model for Training?cited by 4
  11. 2025dMLLM-TTS: Self-Verified and Efficient Test-Time Scaling for Diffusion Multi-Modal Large Language Modelscited by 2
  12. 2024DECOR:Decomposition and Projection of Text Embeddings for Text-to-Image Customizationcited by 1
  13. 2025Accelerating Inference of Masked Image Generators via Reinforcement Learningcited by 1
  14. 2024Controllable Image Generation with Composed Parallel Token Predictioncited by 0
  15. 2024Sustainable techniques to improve Data Quality for training image-based explanatory models for Recommender Systemscited by 0
  16. 2024Multi-Style Facial Sketch Synthesis through Masked Generative Modelingcited by 0
  17. 2025Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Modelscited by 0
  18. 2026Controllable Image Generation with Composed Parallel Token Predictioncited by 0
  19. 2026Dissect and Prune: Enhancing Robustness in AI-Generated Image Detectioncited by 0
  20. 2026Persistent Watermarking of Text-to-Image Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Muse: Text-To-Image Generation via Masked Generative Transformers
  2. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths
  3. 2026i1: A Simple and Fully Open Recipe for Strong Text-to-Image Models
  4. 2024Image Regeneration: Evaluating Text-to-Image Model via Generating Identical Image with Multimodal Large Language Models
  5. 2024Training-Free Sketch-Guided Diffusion with Latent Optimization
  6. 2026Na"ive PAINE: Lightweight Text-to-Image Generation Improvement with Prompt Evaluation
  7. 2026LGTM: Training-Free Light-Guided Text-to-Image Diffusion Model via Initial Noise Manipulation
  8. 2023Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack