mlsanityData to 7 Oct 2026

RAVEN: A Dataset for Relational and Analogical Visual rEasoNing

arXiv 1903.02741 ↗First posted 7 Mar 2019cs.CV cs.AI cs.LGcited by 225

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Cited by 83 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Dramatic progress has been witnessed in basic vision tasks involving low-level perception, such as object recognition, detection, and tracking. Unfortunately, there is still an enormous performance gap between artificial vision systems and human intelligence in terms of higher-level vision problems, especially ones involving reasoning. Earlier attempts in equipping machines with high-level reasoning have hovered around Visual Question Answering (VQA), one typical task associating vision and language understanding. In this work, we propose a new dataset, built in the context of Raven's Progressive Matrices (RPM) and aimed at lifting machine intelligence by associating vision with structural, relational, and analogical reasoning in a hierarchical representation. Unlike previous works in measuring abstract reasoning using RPM, we establish a semantic link between vision and reasoning by providing structure representation. This addition enables a new type of abstract reasoning by jointly operating on the structure representation. Machine reasoning ability using modern computer vision is evaluated in this newly proposed dataset. Additionally, we also provide human performance as a reference. Finally, we show consistent improvement across all models by incorporating a simple neural module that combines visual understanding and structure reasoning.

Key facts. Cited by 225 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Mar 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 28; 2022: 35; 2023: 35; 2024: 48; 2025: 49; 2026: 30.

225 papers.

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  1. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,669
  2. 2024Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMscited by 822
  3. 2025R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalizationcited by 364
  4. 2024What matters when building vision-language models?cited by 321
  5. 2022Emergent Analogical Reasoning in Large Language Modelscited by 239
  6. 2024CogVLM2: Visual Language Models for Image and Video Understandingcited by 214
  7. 2023MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learningcited by 171
  8. 2024Building and better understanding vision-language models: insights and future directionscited by 169
  9. 2024Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoningcited by 136
  10. 2024MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scalecited by 125
  11. 2024NVLM: Open Frontier-Class Multimodal LLMscited by 124
  12. 2022Evaluating and Inducing Personality in Pre-trained Language Modelscited by 122
38 more
  1. 2022EgoTaskQA: Understanding Human Tasks in Egocentric Videoscited by 112
  2. 2021Abstraction and Analogy-Making in Artificial Intelligencecited by 103
  3. 2025VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Modelscited by 102
  4. 2023The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domaincited by 97
  5. 2022Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoningcited by 90
  6. 2024A Survey on Benchmarks of Multimodal Large Language Modelscited by 81
  7. 2025Zebra-CoT: A Dataset for Interleaved Vision Language Reasoningcited by 78
  8. 2022A Neuro-vector-symbolic Architecture for Solving Raven's Progressive Matricescited by 64
  9. 2024MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Modelscited by 61
  10. 2021StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objectscited by 57
  11. 2024CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputscited by 56
  12. 2021Recent Advances of Continual Learning in Computer Vision: An Overviewcited by 55
  13. 2024PuzzleVQA: Diagnosing Multimodal Reasoning Challenges of Language Models with Abstract Visual Patternscited by 54
  14. 2023Large Language Models Are Not Strong Abstract Reasonerscited by 52
  15. 2025FineVision: Open Data Is All You Needcited by 51
  16. 2021A Review on Explainability in Multimodal Deep Neural Netscited by 46
  17. 2024A Survey on Evaluation of Multimodal Large Language Modelscited by 46
  18. 2025FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocitiescited by 46
  19. 2021Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Executioncited by 43
  20. 2022A Benchmark for Compositional Visual Reasoningcited by 43
  21. 2022The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoningcited by 38
  22. 2022Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matricescited by 37
  23. 2021PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoningcited by 34
  24. 2022Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactionscited by 34
  25. 2022A Review of Emerging Research Directions in Abstract Visual Reasoningcited by 33
  26. 2024Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpuscited by 32
  27. 2024GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoningcited by 31
  28. 2021ACRE: Abstract Causal REasoning Beyond Covariationcited by 30
  29. 2024MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learningcited by 30
  30. 2024What is the Visual Cognition Gap between Humans and Multimodal LLMs?cited by 30
  31. 2025SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understandingcited by 30
  32. 2025The Curse of CoT: On the Limitations of Chain-of-Thought in In-Context Learningcited by 30
  33. 2021Mobile App Tasks with Iterative Feedback (MoTIF): Addressing Task Feasibility in Interactive Visual Environmentscited by 28
  34. 2025MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Modelscited by 28
  35. 2021Learning Algebraic Representation for Systematic Generalization in Abstract Reasoningcited by 27
  36. 2022On Neural Architecture Inductive Biases for Relational Taskscited by 26
  37. 2025Explain Before You Answer: A Survey on Compositional Visual Reasoningcited by 26
  38. 2022Are Deep Neural Networks SMARTer than Second Graders?cited by 24

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