WiseEdit: Benchmarking Cognition- and Creativity-Informed Image Editing
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Abstract (arXiv)
Recent image editing models boast next-level intelligent capabilities, facilitating cognition- and creativity-informed image editing. Yet, existing benchmarks provide too narrow a scope for evaluation, failing to holistically assess these advanced abilities. To address this, we introduce WiseEdit, a knowledge-intensive benchmark for comprehensive evaluation of cognition- and creativity-informed image editing, featuring deep task depth and broad knowledge breadth. Drawing an analogy to human cognitive creation, WiseEdit decomposes image editing into three cascaded steps, i.e., Awareness, Interpretation, and Imagination, each corresponding to a task that poses a challenge for models to complete at the specific step. It also encompasses complex tasks, where none of the three steps can be finished easily. Furthermore, WiseEdit incorporates three fundamental types of knowledge: Declarative, Procedural, and Metacognitive knowledge. Ultimately, WiseEdit comprises 1,220 test cases, objectively revealing the limitations of SoTA image editing models in knowledge-based cognitive reasoning and creative composition capabilities. The benchmark, evaluation code, and the generated images of each model will be made publicly available soon. Project Page: https://qnancy.github.io/wiseedit_project_page/.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 40 of its 53 references that are in the map. First posted on arXiv 29 Nov 2025.
Builds on
40 of 53 references.
References · 40
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2023GPT-4 Technical Reportcited by 18,396
- 2022Scalable Diffusion Models with Transformerscited by 6,054
- 2025Qwen2.5-VL Technical Reportcited by 5,587
- 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
- 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,611
- 2025Qwen-Image Technical Reportcited by 1,044
- 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 1,006
- 2025Emerging Properties in Unified Multimodal Pretrainingcited by 897
- 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 812
- 2023MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editingcited by 624
- 2025Step1X-Edit: A Practical Framework for General Image Editingcited by 429
28 more
- 2024OmniGen: Unified Image Generationcited by 394
- 2024UltraEdit: Instruction-based Fine-Grained Image Editing at Scalecited by 268
- 2025OmniGen2: Towards Instruction-Aligned Multimodal Generationcited by 253
- 2025Seedream 4.0: Toward Next-generation Multimodal Image Generationcited by 249
- 2024AnyEdit: Mastering Unified High-Quality Image Editing for Any Ideacited by 241
- 2025WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generationcited by 204
- 2025In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformercited by 204
- 2025HunyuanImage 3.0 Technical Reportcited by 149
- 2023Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Codecited by 145
- 2025HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformercited by 141
- 2025X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Againcited by 112
- 2025Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generationcited by 100
- 2025Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editingcited by 99
- 2025ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generationcited by 97
- 2023Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructionscited by 77
- 2025KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Modelscited by 71
- 2025Uni-cot: Towards Unified Chain-of-Thought Reasoning Across Text and Visioncited by 56
- 2025BLIP3o-NEXT: Next Frontier of Native Image Generationcited by 54
- 2025DreamOmni2: Multimodal Instruction-based Editing and Generationcited by 38
- 2025Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?cited by 34
- 2025Selftok: Discrete Visual Tokens of Autoregression, by Diffusion, and for Reasoningcited by 33
- 2024Auto-Encoding Morph-Tokens for Multimodal LLMcited by 30
- 2025Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokenscited by 28
- 2024Multi-Reward as Condition for Instruction-based Image Editingcited by 20
- 2024Towards Unified Multimodal Editing with Enhanced Knowledge Collaborationcited by 18
- 2025FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RLcited by 13
- 2025Janus-Pro-R1: Advancing Collaborative Visual Comprehension and Generation via Reinforcement Learningcited by 9
- 2023Improving Vision Anomaly Detection with the Guidance of Language Modalitycited by 7
Built on by
Citing papers per year: 2025: 1; 2026: 10.
11 papers.
- 2026Unified Personalized Understanding, Generating and Editingcited by 8
- 2026Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modelingcited by 6
- 2026Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Frameworkcited by 5
- 2026PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Taskscited by 4
- 2026G2TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Modelscited by 3
- 2026PhyEditBench: A Real-World Multi-Stage Benchmark for Physics-Aware Image Editingcited by 3
- 2026CPI-Bench: A Comprehensive, Practical and Intelligent Benchmark for Real-World Image Editingcited by 3
- 2026ViGoR-Bench: How Far Are Visual Generative Models From Zero-Shot Visual Reasoners?cited by 2
- 2025OmniMoGen: Unifying Human Motion Generation via Learning from Interleaved Text-Motion Instructionscited by 1
- 2026ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesiscited by 1
- 2026InfoEdit: Probing Global Layout Reasoning in Infographic Editingcited by 0
- 2026InfoEdit: Probing Global Layout Reasoning in Infographic Editing27 Sep 2026
- 2026CPI-Bench: A Comprehensive, Practical and Intelligent Benchmark for Real-World Image Editing14 Aug 2026
- 2026ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesis21 Jul 2026
- 2026PhyEditBench: A Real-World Multi-Stage Benchmark for Physics-Aware Image Editing25 Jun 2026
- 2026Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework17 Jun 2026
- 2026Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling13 May 2026
- 2026G2TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models12 May 2026
- 2026ViGoR-Bench: How Far Are Visual Generative Models From Zero-Shot Visual Reasoners?26 Mar 2026
- 2026PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks6 Feb 2026
- 2026Unified Personalized Understanding, Generating and Editing11 Jan 2026
- 2025OmniMoGen: Unifying Human Motion Generation via Learning from Interleaved Text-Motion Instructions22 Dec 2025