mlsanityData to 7 Oct 2026

SEED-Data-Edit Technical Report: A Hybrid Dataset for Instructional Image Editing

arXiv 2405.04007 ↗First posted 7 May 2024cs.CVcited by 97

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Cited by 23 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this technical report, we introduce SEED-Data-Edit: a unique hybrid dataset for instruction-guided image editing, which aims to facilitate image manipulation using open-form language. SEED-Data-Edit is composed of three distinct types of data: (1) High-quality editing data produced by an automated pipeline, ensuring a substantial volume of diverse image editing pairs. (2) Real-world scenario data collected from the internet, which captures the intricacies of user intentions for promoting the practical application of image editing in the real world. (3) High-precision multi-turn editing data annotated by humans, which involves multiple rounds of edits for simulating iterative editing processes. The combination of these diverse data sources makes SEED-Data-Edit a comprehensive and versatile dataset for training language-guided image editing model. We fine-tune a pretrained Multimodal Large Language Model (MLLM) that unifies comprehension and generation with SEED-Data-Edit. The instruction tuned model demonstrates promising results, indicating the potential and effectiveness of SEED-Data-Edit in advancing the field of instructional image editing. The datasets are released in https://huggingface.co/datasets/AILab-CVC/SEED-Data-Edit.

Key facts. Cited by 97 papers in the map (data through 7 Oct 2026). Builds on 18 of its 23 references that are in the map. First posted on arXiv 7 May 2024.

Builds on

18 of 23 references.

References · 18

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  5. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  6. 2023Improved Baselines with Visual Instruction Tuningcited by 4,362
  7. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  8. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  9. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  10. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897
  11. 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 854
  12. 2021Resolution-robust Large Mask Inpainting with Fourier Convolutionscited by 730
6 more
  1. 2023MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editingcited by 615
  2. 2024SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generationcited by 328
  3. 2023Emu Edit: Precise Image Editing via Recognition and Generation Taskscited by 321
  4. 2023JourneyDB: A Benchmark for Generative Image Understandingcited by 203
  5. 2024HQ-Edit: A High-Quality Dataset for Instruction-based Image Editingcited by 191
  6. 2023Guiding Instruction-based Image Editing via Multimodal Large Language Modelscited by 182

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 13; 2025: 56; 2026: 28.

97 papers.

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  1. 2025Emerging Properties in Unified Multimodal Pretrainingcited by 855
  2. 2025VACE: All-in-One Video Creation and Editingcited by 467
  3. 2025Step1X-Edit: A Practical Framework for General Image Editingcited by 417
  4. 2024OmniGen: Unified Image Generationcited by 388
  5. 2025OmniGen2: Towards Instruction-Aligned Multimodal Generationcited by 241
  6. 2024AnyEdit: Mastering Unified High-Quality Image Editing for Any Ideacited by 235
  7. 2025ImgEdit: A Unified Image Editing Dataset and Benchmarkcited by 225
  8. 2024Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretrainingcited by 148
  9. 2025GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editingcited by 103
  10. 2025ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generationcited by 94
  11. 2025Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Modelscited by 89
  12. 2025Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunitiescited by 81
38 more
  1. 2025KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Modelscited by 69
  2. 2025Ovis-U1 Technical Reportcited by 65
  3. 2025Ming-Omni: A Unified Multimodal Model for Perception and Generationcited by 62
  4. 2024ACE: All-round Creator and Editor Following Instructions via Diffusion Transformercited by 56
  5. 2025EditVerse: Unifying Image and Video Editing and Generation with In-Context Learningcited by 53
  6. 2025OpenVE-3M: A Large-Scale High-Quality Dataset for Instruction-Guided Video Editingcited by 50
  7. 2025EditAR: Unified Conditional Generation with Autoregressive Modelscited by 40
  8. 2025VEGGIE: Instructional Editing and Reasoning Video Concepts with Grounded Generationcited by 39
  9. 2025DreamOmni2: Multimodal Instruction-based Editing and Generationcited by 35
  10. 2025NoHumansRequired: Autonomous High-Quality Image Editing Triplet Miningcited by 33
  11. 2024PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructionscited by 31
  12. 2025FireEdit: Fine-grained Instruction-based Image Editing via Region-aware Vision Language Modelcited by 31
  13. 2024OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generationcited by 30
  14. 2024HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editingcited by 29
  15. 2025X2Edit: Revisiting Arbitrary-Instruction Image Editing through Self-Constructed Data and Task-Aware Representation Learningcited by 24
  16. 2025PhotoDoodle: Learning Artistic Image Editing from Few-Shot Pairwise Datacited by 23
  17. 2025Visual Autoregressive Modeling for Instruction-Guided Image Editingcited by 21
  18. 2024PUMA: Empowering Unified MLLM with Multi-granular Visual Generationcited by 20
  19. 2024Multi-Reward as Condition for Instruction-based Image Editingcited by 20
  20. 2025ComplexBench-Edit: Benchmarking Complex Instruction-Driven Image Editing via Compositional Dependenciescited by 20
  21. 2025UniVG: A Generalist Diffusion Model for Unified Image Generation and Editingcited by 19
  22. 2025ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid Motionscited by 19
  23. 2025SuperEdit: Rectifying and Facilitating Supervision for Instruction-Based Image Editingcited by 18
  24. 2026Agent Banana: High-Fidelity Image Editing with Agentic Thinking and Toolingcited by 17
  25. 2025VIVA: VLM-Guided Instruction-Based Video Editing with Reward Optimizationcited by 16
  26. 2025Query-Kontext: An Unified Multimodal Model for Image Generation and Editingcited by 15
  27. 2025MIRA: Multimodal Iterative Reasoning Agent for Image Editingcited by 15
  28. 2024MobA: Multifaceted Memory-Enhanced Adaptive Planning for Efficient Mobile Task Automationcited by 14
  29. 2025CompBench: Benchmarking Complex Instruction-guided Image Editingcited by 14
  30. 2025Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interactioncited by 13
  31. 2025Learning an Image Editing Model without Image Editing Pairscited by 13
  32. 2025EditMGT: Unleashing Potentials of Masked Generative Transformers in Image Editingcited by 12
  33. 2025EasyV2V: A High-quality Instruction-based Video Editing Frameworkcited by 11
  34. 2025MIGE: Mutually Enhanced Multimodal Instruction-Based Image Generation and Editingcited by 10
  35. 2025DreamVE: Unified Instruction-based Image and Video Editingcited by 9
  36. 2025UnicEdit-10M: A Dataset and Benchmark Breaking the Scale-Quality Barrier via Unified Verification for Reasoning-Enriched Editscited by 9
  37. 2026SAMA: Factorized Semantic Anchoring and Motion Alignment for Instruction-Guided Video Editingcited by 8
  38. 2025Semantic Context Matters: Improving Conditioning for Autoregressive Modelscited by 7

50 most cited of 97 All 97 (JSON)

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  1. 2025Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing
  2. 2025GPT-IMAGE-EDIT-1.5M: A Million-Scale, GPT-Generated Image Dataset
  3. 2025MultiEdit: Advancing Instruction-based Image Editing on Diverse and Challenging Tasks
  4. 2024InsightEdit: Towards Better Instruction Following for Image Editing
  5. 2026Instruction-based Image Editing: A Survey on Data, Models, Evaluation, and Applications
  6. 2025Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder
  7. 2023SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models
  8. 2026Instruction-based Image Editing with Planning, Reasoning, and Generation