mlsanityData to 7 Oct 2026

M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understanding

arXiv 2601.08758 ↗First posted 13 Jan 2026eess.IV cs.CVcited by 6

On the map: LLM reasoning → Clinical and biomedical applications

also in 1 more
Abstract (arXiv)

Chain-of-Thought (CoT) reasoning has proven effective in enhancing large language models by encouraging step-by-step intermediate reasoning, and recent advances have extended this paradigm to Multimodal Large Language Models (MLLMs). In the medical domain, where diagnostic decisions depend on nuanced visual cues and sequential reasoning, CoT aligns naturally with clinical thinking processes. However, current benchmarks for medical image understanding generally focus on the final answer while ignoring the reasoning path. Such opaque reasoning processes lack reliable bases for judgment, making it difficult to assist doctors in diagnosis. To address this gap, we introduce a new M3CoTBench benchmark specifically designed to evaluate the correctness, efficiency, impact, and consistency of CoT reasoning in medical image understanding. M3CoTBench features 1) a diverse, multi-level difficulty dataset covering 24 examination types, 2) 13 varying-difficulty tasks, 3) a suite of CoT-specific evaluation metrics (correctness, efficiency, impact, and consistency) tailored to clinical reasoning, and 4) a performance analysis of multiple MLLMs. M3CoTBench systematically evaluates CoT reasoning across diverse medical imaging tasks, revealing current limitations of MLLMs in generating reliable and clinically interpretable reasoning, and aims to foster the development of transparent, trustworthy, and diagnostically accurate AI systems for healthcare. Project page at https://juntaojianggavin.github.io/projects/M3CoTBench/.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 27 of its 107 references that are in the map. First posted on arXiv 13 Jan 2026.

Builds on

27 of 107 references.

Closest ancestors · 1

Same direction, newest first

  1. 2025Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning8 Jun

Other references · 26

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  4. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,669
  5. 2025Qwen3-VL Technical Reportcited by 2,534
  6. 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiencycited by 1,419
  7. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 657
  8. 2023BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairscited by 506
  9. 2020PathVQA: 30000+ Questions for Medical Visual Question Answeringcited by 467
  10. 2024LLaVA-CoT: Let Vision Language Models Reason Step-by-Stepcited by 446
  11. 2025MedGemma Technical Reportcited by 398
  12. 2024HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scalecited by 194
14 more
  1. 2025Multimodal Chain-of-Thought Reasoning: A Comprehensive Surveycited by 176
  2. 20192017 Robotic Instrument Segmentation Challengecited by 166
  3. 2025MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiencycited by 123
  4. 2025HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptationcited by 112
  5. 2024Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Modelscited by 65
  6. 2025When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMscited by 51
  7. 2024TextCoT: Zoom In for Enhanced Multimodal Text-Rich Image Understandingcited by 37
  8. 2025Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Modelscited by 24
  9. 2024Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopycited by 16
  10. 2024FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Taskscited by 11
  11. 2021FetReg: Placental Vessel Segmentation and Registration in Fetoscopy Challenge Datasetcited by 8
  12. 2023DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Imagescited by 5
  13. 2023Stress Testing Chain-of-Thought Prompting for Large Language Modelscited by 2
  14. 2025A Retrospective Systematic Study on Hierarchical Sparse Query Transformer-assisted Ultrasound Screening for Early Hepatocellular Carcinomacited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026MedMASLab: A Unified Orchestration Framework for Benchmarking Multimodal Medical Multi-Agent Systemscited by 3
  2. 2026OpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Modelscited by 1
  3. 2026MuteBench: Modality Unavailability Tolerance Evaluation for Incomplete Multimodal Fusioncited by 0
  4. 2026VITAL: Visual-Semantic Dual Supervision for Enhanced and Interpretable Latent Reasoning in Medical MLLMscited by 0
  5. 2026Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Modelscited by 0
  6. 2026Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMscited by 0

Similar, not cited

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  1. 2026Beyond Visual Cues: CoT-Enhanced Reasoning for Semi-supervised Medical Image Segmentation
  2. 2026Step-CoT: Stepwise Visual Chain-of-Thought for Medical Visual Question Answering
  3. 2025S-Chain: Structured Visual Chain-of-Thought For Medicine
  4. 2024MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration
  5. 2026ClinCoT: Clinical-Aware Visual Chain-of-Thought for Medical Vision Language Models
  6. 2025Reasoning Visual Language Model for Chest X-Ray Analysis
  7. 2025MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
  8. 2025Chiron-o1: Igniting Multimodal Large Language Models towards Generalizable Medical Reasoning via Mentor-Intern Collaborative Search