mlsanityData to 14 Oct 2026

GenExam: A Multidisciplinary Text-to-Image Exam

arXiv 2509.14232 ↗First posted 17 Sep 2025cs.CVcited by 22

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Abstract (arXiv)

Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style benchmarks mainly focus on understanding and reasoning tasks, and current generation benchmarks emphasize the illustration of world knowledge and visual concepts, neglecting the evaluation of rigorous drawing exams. We introduce GenExam, the first benchmark for multidisciplinary text-to-image exams, featuring 1,000 samples across 10 subjects with exam-style prompts organized under a four-level taxonomy. Each problem is equipped with ground-truth images and fine-grained scoring points to enable a precise evaluation of semantic correctness and visual plausibility. Experiments on 17 text-to-image and unified models demonstrate the great challenge of GenExam and the huge gap where open-source models consistently lag behind the leading closed-source ones. By framing image generation as an exam, GenExam offers a rigorous assessment of models' ability to integrate understanding, reasoning, and generation, providing insights for on the path to intelligent generative models. Our benchmark and evaluation code are released at https://github.com/OpenGVLab/GenExam.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 44 of its 78 references that are in the map. First posted on arXiv 17 Sep 2025.

Builds on

44 of 78 references.

References · 44

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  4. 2025Qwen2.5-VL Technical Reportcited by 5,587
  5. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  6. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,424
  7. 2023MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIcited by 2,080
  8. 2022Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answeringcited by 1,919
  9. 2024MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmarkcited by 1,848
  10. 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiencycited by 1,510
  11. 2025Qwen-Image Technical Reportcited by 1,044
  12. 2024Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Predictioncited by 1,023
32 more
  1. 2025Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?cited by 982
  2. 2023GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignmentcited by 972
  3. 2025Emerging Properties in Unified Multimodal Pretrainingcited by 897
  4. 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 812
  5. 2024Emu3: Next-Token Prediction is All You Needcited by 781
  6. 2024Autoregressive Model Beats Diffusion: Llama for Scalable Image Generationcited by 777
  7. 2023AGIEval: A Human-Centric Benchmark for Evaluating Foundation Modelscited by 716
  8. 2024MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmarkcited by 512
  9. 2024Evaluating Text-to-Visual Generation with Image-to-Text Generationcited by 474
  10. 2025BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Datasetcited by 376
  11. 2025Show-o2: Improved Native Unified Multimodal Modelscited by 250
  12. 2025WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generationcited by 204
  13. 2025Seedream 3.0 Technical Reportcited by 154
  14. 2025HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformercited by 141
  15. 2025Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editingcited by 99
  16. 2025OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generationcited by 87
  17. 2024Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-trainingcited by 82
  18. 2025KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Modelscited by 71
  19. 2024Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?cited by 52
  20. 2025Kwai Keye-VL Technical Reportcited by 47
  21. 2024SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Foldingcited by 42
  22. 2025T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generationcited by 38
  23. 2024PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Modelscited by 36
  24. 2025R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluationcited by 34
  25. 2024MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Modelscited by 33
  26. 2025SpaCE-10: A Comprehensive Benchmark for Multimodal Large Language Models in Compositional Spatial Intelligencecited by 23
  27. 2025WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generationcited by 20
  28. 2025SridBench: Benchmark of Scientific Research Illustration Drawing of Image Generation Modelcited by 19
  29. 2025MMMG: A Massive, Multidisciplinary, Multi-Tier Generation Benchmark for Text-to-Image Reasoningcited by 16
  30. 2025Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Modelscited by 13
  31. 2025Parameter-Inverted Image Pyramid Networks for Visual Perception and Multimodal Understandingcited by 8
  32. 2025Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?cited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 21.

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  1. 2026InternVL-U: Democratizing Unified Multimodal Models for Understanding, Reasoning, Generation and Editingcited by 28
  2. 2026PresentBench: A Fine-Grained Rubric-Based Benchmark for Slide Generationcited by 14
  3. 2026Multimodal OCR: Parse Anything from Documentscited by 14
  4. 2026BizGenEval: A Systematic Benchmark for Commercial Visual Content Generationcited by 11
  5. 2025TextEditBench: Evaluating Reasoning-aware Text Editing Beyond Renderingcited by 8
  6. 2026GRADE: Benchmarking Discipline-Informed Reasoning in Image Editingcited by 7
  7. 2026Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modelingcited by 5
  8. 2026PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Taskscited by 4
  9. 2026SIQA: Toward Reliable Scientific Image Quality Assessmentcited by 4
  10. 2026Gym-V: A Unified Vision Environment System for Agentic Vision Researchcited by 3
  11. 2026Socratic-Geo: Synthetic Data Generation and Geometric Reasoning via Multi-Agent Interactioncited by 2
  12. 2026How RL Unlocks the Aha Moment in Geometric Interleaved Reasoningcited by 2
10 more
  1. 2026ViGoR-Bench: How Far Are Visual Generative Models From Zero-Shot Visual Reasoners?cited by 2
  2. 2026OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibrationcited by 2
  3. 2026MathGen: Revealing the Illusion of Mathematical Competence through Text-to-Image Generationcited by 1
  4. 2026Towards Characterizing Scientific Image Utility and Upgradabilitycited by 1
  5. 2026DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editingcited by 1
  6. 2026Draw2Think: Harnessing Geometry Reasoning through Constraint Engine Interactioncited by 0
  7. 2026Towards Physics-Faithful Generation of Scientific Diagramscited by 0
  8. 2026MetaReason: Precise Interleaved Multimodal Reasoning via Editing Meta Information for Solving Geometry Problemscited by 0
  9. 2026SciGen-Verifier: A Multimodal Reasoner for Explainable Verification in Scientific Image Generationcited by 0
  10. 2026Reasoning-Informed Visual Editingcited by 0