mlsanityData to 14 Oct 2026

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

arXiv 2503.07265 ↗First posted 10 Mar 2025cs.CV cs.AI cs.CLcited by 204

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Cited by 34 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evaluation standards predominantly focus on image realism and shallow text-image alignment, lacking a comprehensive assessment of complex semantic understanding and world knowledge integration in text-to-image generation. To address this challenge, we propose WISE, the first benchmark specifically designed for World Knowledge-Informed Semantic Evaluation. WISE moves beyond simple word-pixel mapping by challenging models with 1000 meticulously crafted prompts across 25 subdomains in cultural common sense, spatio-temporal reasoning, and natural science. To overcome the limitations of traditional CLIP metric, we introduce WiScore, a novel quantitative metric for assessing knowledge-image alignment. Through comprehensive testing of 20 models (10 dedicated T2I models and 10 unified multimodal models) using 1,000 structured prompts spanning 25 subdomains, our findings reveal significant limitations in their ability to effectively integrate and apply world knowledge during image generation, highlighting critical pathways for enhancing knowledge incorporation and application in next-generation T2I models. Code and data are available at hrefhttps://github.com/PKU-YuanGroup/WISEPKU-YuanGroup/WISE.

Key facts. Cited by 204 papers in the map (data through 14 Oct 2026). Builds on 47 of its 74 references that are in the map. First posted on arXiv 10 Mar 2025.

Builds on

47 of 74 references.

References · 47

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  5. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  7. 2017Neural Discrete Representation Learningcited by 4,712
  8. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,356
  9. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
  10. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
  11. 2023A Survey of Large Language Modelscited by 2,576
  12. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,424
35 more
  1. 2023ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generationcited by 1,045
  2. 2024Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Predictioncited by 1,023
  3. 2023GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignmentcited by 972
  4. 2024Chameleon: Mixed-Modal Early-Fusion Foundation Modelscited by 927
  5. 2023Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesiscited by 890
  6. 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 812
  7. 2024Emu3: Next-Token Prediction is All You Needcited by 781
  8. 2024Autoregressive Model Beats Diffusion: Llama for Scalable Image Generationcited by 777
  9. 2024Show-o: One Single Transformer to Unify Multimodal Understanding and Generationcited by 752
  10. 2022When and why vision-language models behave like bags-of-words, and what to do about it?cited by 610
  11. 2024Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Modelcited by 483
  12. 2024ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignmentcited by 475
  13. 2024Evaluating Text-to-Visual Generation with Image-to-Text Generationcited by 474
  14. 2024Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generationcited by 457
  15. 2024SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generationcited by 331
  16. 2024Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesiscited by 304
  17. 2024Open-Sora Plan: Open-Source Large Video Generation Modelcited by 296
  18. 2024VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generationcited by 295
  19. 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 265
  20. 2024Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generationcited by 256
  21. 2024MetaMorph: Multimodal Understanding and Generation via Instruction Tuningcited by 206
  22. 2024Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokenscited by 147
  23. 2024GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generationcited by 135
  24. 2024LMFusion: Adapting Pretrained Language Models for Multimodal Generationcited by 120
  25. 2023KoLA: Carefully Benchmarking World Knowledge of Large Language Modelscited by 85
  26. 2024Dual Diffusion for Unified Image Generation and Understandingcited by 76
  27. 2024ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficultycited by 61
  28. 2024Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?cited by 52
  29. 2024Multimodal Latent Language Modeling with Next-Token Diffusioncited by 48
  30. 2024Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Headscited by 44
  31. 2024SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Foldingcited by 42
  32. 2024PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Modelscited by 36
  33. 2024Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Surveycited by 27
  34. 2024Next Patch Prediction for Autoregressive Visual Generationcited by 26
  35. 2024Evaluating the Generation of Spatial Relations in Text and Image Generative Modelscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 91; 2026: 113.

204 papers.

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  1. 2025Emerging Properties in Unified Multimodal Pretrainingcited by 897
  2. 2025MMaDA: Multimodal Large Diffusion Language Modelscited by 250
  3. 2025Show-o2: Improved Native Unified Multimodal Modelscited by 250
  4. 2025Transfer between Modalities with MetaQueriescited by 236
  5. 2025T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoTcited by 166
  6. 2025LongCat-Image Technical Reportcited by 100
  7. 2025Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editingcited by 99
  8. 2025Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learningcited by 92
  9. 2025OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generationcited by 87
  10. 2025Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunitiescited by 85
  11. 2025Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedbackcited by 79
  12. 2025Harmonizing Visual Representations for Unified Multimodal Understanding and Generationcited by 74
38 more
  1. 2025KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Modelscited by 71
  2. 2025TIIF-Bench: How Does Your T2I Model Follow Your Instructions?cited by 69
  3. 2025UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generationcited by 66
  4. 2025GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generationcited by 58
  5. 2025NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scalecited by 57
  6. 2025Uni-cot: Towards Unified Chain-of-Thought Reasoning Across Text and Visioncited by 56
  7. 2025BLIP3o-NEXT: Next Frontier of Native Image Generationcited by 54
  8. 2025GenEval 2: Addressing Benchmark Drift in Text-to-Image Evaluationcited by 52
  9. 2025Reconstruction Alignment Improves Unified Multimodal Modelscited by 49
  10. 2025SSR: Enhancing Depth Perception in Vision-Language Models via Rationale-Guided Spatial Reasoningcited by 46
  11. 2025OpenUni: A Simple Baseline for Unified Multimodal Understanding and Generationcited by 46
  12. 2025UniLiP: Adapting CLIP for Unified Multimodal Understanding, Generation and Editingcited by 44
  13. 2025DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabulariescited by 42
  14. 2025Interleaving Reasoning for Better Text-to-Image Generationcited by 41
  15. 2025T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generationcited by 38
  16. 2026Beyond Language Modeling: An Exploration of Multimodal Pretrainingcited by 37
  17. 2026LongCat-Next: Lexicalizing Modalities as Discrete Tokenscited by 36
  18. 2025Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?cited by 34
  19. 2025RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmarkcited by 33
  20. 2025VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understandingcited by 32
  21. 2025R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generationcited by 32
  22. 2026SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecturecited by 32
  23. 2025MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPOcited by 30
  24. 2026Gen-Searcher: Reinforcing Agentic Search for Image Generationcited by 30
  25. 2026InternVL-U: Democratizing Unified Multimodal Models for Understanding, Reasoning, Generation and Editingcited by 28
  26. 2025A Survey of Multimodal Hallucination Evaluation and Detectioncited by 27
  27. 2026UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervisioncited by 26
  28. 2025UniGenBench++: A Unified Semantic Evaluation Benchmark for Text-to-Image Generationcited by 25
  29. 2025UniREditBench: A Unified Reasoning-based Image Editing Benchmarkcited by 25
  30. 2025EditThinker: Unlocking Iterative Reasoning for Any Image Editorcited by 25
  31. 2026GenAgent: Scaling Text-to-Image Generation via Agentic Multimodal Reasoningcited by 24
  32. 2026Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generationcited by 23
  33. 2025GenExam: A Multidisciplinary Text-to-Image Examcited by 22
  34. 2025SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Modelscited by 22
  35. 2026Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluationcited by 22
  36. 2025Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Datacited by 21
  37. 2026GEMS: Agent-Native Multimodal Generation with Memory and Skillscited by 21
  38. 2025WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generationcited by 20

50 most cited of 204 All 204 (JSON)

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  1. 2025Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation
  2. 2024KITTEN: A Knowledge-Intensive Evaluation of Image Generation on Visual Entities
  3. 2025CompArt: Operationalizing Aesthetic Alignment in Text-to-Image Generation via Principles of Art
  4. 2025Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation
  5. 2026Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation
  6. 2024Prompt-Consistency Image Generation (PCIG): A Unified Framework Integrating LLMs, Knowledge Graphs, and Controllable Diffusion Models
  7. 2025Culture-TRIP: Culturally-Aware Text-to-Image Generation with Iterative Prompt Refinement
  8. 2025VISTAR:A User-Centric and Role-Driven Benchmark for Text-to-Image Evaluation