mlsanityData to 7 Oct 2026

Thinking with Comics: Enhancing Multimodal Reasoning through Structured Visual Storytelling

arXiv 2602.02453 ↗First posted 2 Feb 2026cs.AIcited by 0

On the map: LLM reasoning → Multimodal reasoning

Abstract (arXiv)

Chain-of-Thought reasoning has driven large language models to extend from thinking with text to thinking with images and videos. However, different modalities still have clear limitations: static images struggle to represent temporal structure, while videos introduce substantial redundancy and computational cost. In this work, we propose Thinking with Comics, a visual reasoning paradigm that uses comics as a high information-density medium positioned between images and videos. Comics preserve temporal structure, embedded text, and narrative coherence while requiring significantly lower reasoning cost. We systematically study two reasoning paths based on comics and evaluate them on a range of reasoning tasks and long-context understanding tasks. Experimental results show that Thinking with Comics outperforms Thinking with Images on multi-step temporal and causal reasoning tasks, while remaining substantially more efficient than Thinking with Video. Further analysis indicates that different comic narrative structures and styles consistently affect performance across tasks, suggesting that comics serve as an effective intermediate visual representation for improving multimodal reasoning.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal reasoning, one of 17 directions in LLM reasoning. Builds on 16 of its 40 references that are in the map. First posted on arXiv 2 Feb 2026.

Builds on

16 of 40 references.

Closest ancestors · 7

Same direction, newest first

  1. 2025Thinking with Video: Video Generation as a Promising Multimodal Reasoning Paradigm6 Nov
  2. 2025Visual Thoughts: A Unified Perspective of Understanding Multimodal Chain-of-Thought21 May
  3. 2025Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey16 Mar
  4. 2025Visual-RFT: Visual Reinforcement Fine-Tuning3 Mar
  5. 2025Imagine while Reasoning in Space: Multimodal Visualization-of-Thought13 Jan
  6. 2023MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts3 Oct
  7. 2023Multimodal Chain-of-Thought Reasoning in Language Models2 Feb

Other references · 9

  1. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
  3. 2025Qwen3 Technical Reportcited by 8,195
  4. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  5. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  6. 2024GPT-4o System Cardcited by 4,467
  7. 2025OpenAI GPT-5 System Cardcited by 910
  8. 2023DreamLLM: Synergistic Multimodal Comprehension and Creationcited by 296
  9. 2024CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeamingcited by 27

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Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Towards Faithful Reasoning in Comics for Small MLLMs
  2. 2024One missing piece in Vision and Language: A Survey on Comics Understanding
  3. 2026Optical Reasoning: Rethinking Images as an Expressive Reasoning Medium Beyond Text
  4. 2025Thinking with Generated Images
  5. 2025ThinkMorph: Emergent Properties in Multimodal Interleaved Chain-of-Thought Reasoning
  6. 2025Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
  7. 2025Thinking with Visual Abstract: Enhancing Multimodal Reasoning via Visual Abstraction
  8. 2026See2Think: Do Multimodal Models Really Use Intermediate Visual States?