mlsanityData to 7 Oct 2026

Reasoning Limitations of Multimodal Large Language Models. A Case Study of Bongard Problems

arXiv 2411.01173 ↗First posted 2 Nov 2024cs.AI cs.CV cs.LGcited by 15

On the map: LLM reasoning → Multimodal reasoning

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Abstract (arXiv)

Abstract visual reasoning (AVR) involves discovering shared concepts across images through analogy, akin to solving IQ test problems. Bongard Problems (BPs) remain a key challenge in AVR, requiring both visual reasoning and verbal description. We investigate whether multimodal large language models (MLLMs) can solve BPs by formulating a set of diverse MLLM-suited solution strategies and testing 4 proprietary and 4 open-access models on 3 BP datasets featuring synthetic (classic BPs) and real-world (Bongard HOI and Bongard-OpenWorld) images. Despite some successes on real-world datasets, MLLMs struggle with synthetic BPs. To explore this gap, we introduce Bongard-RWR, a dataset representing synthetic BP concepts using real-world images. Our findings suggest that weak MLLM performance on classical BPs is not due to the domain specificity, but rather comes from their general AVR limitations. Code and dataset are available at: https://github.com/pavonism/bongard-rwr

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Placed in Multimodal reasoning, one of 17 directions in LLM reasoning. Builds on 16 of its 91 references that are in the map. First posted on arXiv 2 Nov 2024.

Builds on

16 of 91 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?25 Oct

Other references · 15

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2020Scaling Laws for Neural Language Modelscited by 6,411
  3. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
  4. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,175
  5. 2023Mistral 7Bcited by 3,065
  6. 2023Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyondcited by 2,179
  7. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,883
  8. 2019On the Measure of Intelligencecited by 129
  9. 2024What is the Visual Cognition Gap between Humans and Multimodal LLMs?cited by 30
  10. 2018Solving Bongard Problems with a Visual Language and Pragmatic Reasoningcited by 21
  11. 2022Evaluating Understanding on Conceptual Abstraction Benchmarkscited by 13
  12. 2021Visual analogy: Deep learning versus compositional modelscited by 11
3 more
  1. 2024MindSet: Vision. A toolbox for testing DNNs on key psychological experimentscited by 8
  2. 2021Using Program Synthesis and Inductive Logic Programming to solve Bongard Problemscited by 6
  3. 2024The Cognitive Capabilities of Generative AI: A Comparative Analysis with Human Benchmarkscited by 6

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  1. 2026Bongards at the Boundary of Perception and Reasoning: Programs or Language?
  2. 2025VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning
  3. 2025ImageNet-Think-250K: A Large-Scale Synthetic Dataset for Multimodal Reasoning for Vision Language Models
  4. 2025VisualQuest: A Benchmark for Abstract Visual Reasoning in MLLMs
  5. 2025LENS: Multi-level Evaluation of Multimodal Reasoning with Large Language Models
  6. 2025On Data Synthesis and Post-training for Visual Abstract Reasoning
  7. 2025Revisiting Visual Understanding in Multimodal Reasoning through a Lens of Image Perturbation
  8. 2025VGR: Visual Grounded Reasoning