mlsanityData to 7 Oct 2026

Benchmarking the Thinking Mode of Multimodal Large Language Models in Clinical Tasks

arXiv 2511.03328 ↗First posted 5 Nov 2025cs.CL cs.AI cs.CVcited by 2

On the map: LLM reasoning → Clinical and biomedical applications

also in 1 more
Abstract (arXiv)

A recent advancement in Multimodal Large Language Models (MLLMs) research is the emergence of "reasoning MLLMs" that offer explicit control over their internal thinking processes (normally referred as the "thinking mode") alongside the standard "non-thinking mode". This capability allows these models to engage in a step-by-step process of internal deliberation before generating a final response. With the rapid transition to and adoption of these "dual-state" MLLMs, this work rigorously evaluated how the enhanced reasoning processes of these MLLMs impact model performance and reliability in clinical tasks. This paper evaluates the active "thinking mode" capabilities of two leading MLLMs, Seed1.5-VL and Gemini-2.5-Flash, for medical applications. We assessed their performance on four visual medical tasks using VQA-RAD and ROCOv2 datasets. Our findings reveal that the improvement from activating the thinking mode remains marginal compared to the standard non-thinking mode for the majority of the tasks. Their performance on complex medical tasks such as open-ended VQA and medical image interpretation remains suboptimal, highlighting the need for domain-specific medical data and more advanced methods for medical knowledge integration.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 19 of its 38 references that are in the map. First posted on arXiv 5 Nov 2025.

Builds on

19 of 38 references.

Closest ancestors · 1

Same direction, newest first

  1. 2025Can Reasoning LLMs Enhance Clinical Document Classification?10 Apr

Other references · 18

  1. 2025Qwen3 Technical Reportcited by 8,195
  2. 2025Stop Overthinking: A Survey on Efficient Reasoning for Large Language Modelscited by 456
  3. 2025Seed1.5-VL Technical Reportcited by 367
  4. 2024HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scalecited by 194
  5. 2025Reasoning Models Can Be Effective Without Thinkingcited by 182
  6. 2025AdaptThink: Reasoning Models Can Learn When to Thinkcited by 141
  7. 2023XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Modelscited by 61
  8. 2024From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyondcited by 24
  9. 2024AutoRG-Brain: Grounded Report Generation for Brain MRIcited by 23
  10. 2023SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Modelcited by 18
  11. 2025SeqPO-SiMT: Sequential Policy Optimization for Simultaneous Machine Translationcited by 13
  12. 2024DAPE V2: Process Attention Score as Feature Map for Length Extrapolationcited by 10
6 more
  1. 2025Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generationcited by 10
  2. 2025Emerging Cyber Attack Risks of Medical AI Agentscited by 8
  3. 2025SynapseRoute: An Auto-Route Switching Framework on Dual-State Large Language Modelcited by 7
  4. 2025Understanding the Mixture-of-Experts with Nadaraya-Watson Kernelcited by 6
  5. 2025SAS: Simulated Attention Scorecited by 3
  6. 2025Diagnosing Shoulder Disorders Using Multimodal Large Language Models and Consumer-Grade Camerascited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Unveiling the Entropy Dynamics of Chain-of-Thought Reasoningcited by 4
  2. 2026Evaluating Multi-Turn Multimodal Diagnostic Reasoning on Challenging Real-World Clinical Casescited by 0

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  1. 2025Multimodal Large Language Models for Medicine: A Comprehensive Survey
  2. 2025Med-CMR: A Fine-Grained Benchmark Integrating Visual Evidence and Clinical Logic for Medical Complex Multimodal Reasoning
  3. 2024Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning
  4. 2024A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicine
  5. 2024From Text to Multimodality: Exploring the Evolution and Impact of Large Language Models in Medical Practice
  6. 2025Why Text Prevails: Vision May Undermine Multimodal Medical Decision Making
  7. 2025Chiron-o1: Igniting Multimodal Large Language Models towards Generalizable Medical Reasoning via Mentor-Intern Collaborative Search
  8. 2026When Prompts Mislead: Textual Dominance and Diagnostic Bias in MLLMs