title: VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search
summary: Recent advancements in Large Vision-Language Models have showcased remarkable
  capabilities. However, they often falter when confronted with complex reasoning
  tasks that humans typically address through visual aids and deliberate,
  step-by-step thinking. While existing methods have explored text-based slow
  thinking or rudimentary visual assistance, they fall short of capturing the
  intricate, interleaved nature of human visual-verbal reasoning processes. To
  overcome these limitations and inspired by the mechanisms of slow thinking in
  human cognition, we introduce VisuoThink, a novel framework that seamlessly
  integrates visuospatial and linguistic domains. VisuoThink facilitates
  multimodal slow thinking by enabling progressive visual-textual reasoning and
  incorporates test-time scaling through look-ahead tree search. Extensive
  experiments demonstrate that VisuoThink significantly enhances reasoning
  capabilities via inference-time scaling, even without fine-tuning, achieving
  state-of-the-art performance in tasks involving geometry and spatial reasoning.
paper_authors._id: 67fe0d1f3a2e18d214499d3c
paper_authors.name: Yikun Wang
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paper_authors.fullname: Yikun Wang
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paper_authors.name: Siyin Wang
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paper_authors.fullname: Siyin Wang
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paper_authors.user: sinwang
paper_authors._id: 67fe0d1f3a2e18d214499d3e
paper_authors.name: Qinyuan Cheng
paper_authors._id: 67fe0d1f3a2e18d214499d3f
paper_authors.name: Zhaoye Fei
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paper_authors.fullname: Zhaoye Fei
paper_authors.type: user
paper_authors.user: ngc7293
paper_authors._id: 67fe0d1f3a2e18d214499d40
paper_authors.name: Liang Ding
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paper_authors.fullname: Liang Ding
paper_authors.type: user
paper_authors.user: alphadl
paper_authors._id: 67fe0d1f3a2e18d214499d41
paper_authors.name: Qipeng Guo
paper_authors.status: admin_assigned
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paper_authors.avatarUrl: /avatars/a85635d886c7f157b6723dec5c01c030.svg
paper_authors.fullname: Qipeng Guo
paper_authors.type: user
paper_authors.user: QipengGuo
paper_authors._id: 67fe0d1f3a2e18d214499d42
paper_authors.name: Dacheng Tao
paper_authors._id: 67fe0d1f3a2e18d214499d43
paper_authors.name: Xipeng Qiu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-15T08:35:23.363Z
paper_authors._id: 61457b8deff2c9fdb4de4988
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1632381702899-61457b8deff2c9fdb4de4988.jpeg
paper_authors.fullname: Xipeng Qiu
paper_authors.type: user
paper_authors.user: xpqiu
paper_title: VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search
paper_summary: Recent advancements in Large Vision-Language Models have showcased remarkable
  capabilities. However, they often falter when confronted with complex reasoning
  tasks that humans typically address through visual aids and deliberate,
  step-by-step thinking. While existing methods have explored text-based slow
  thinking or rudimentary visual assistance, they fall short of capturing the
  intricate, interleaved nature of human visual-verbal reasoning processes. To
  overcome these limitations and inspired by the mechanisms of slow thinking in
  human cognition, we introduce VisuoThink, a novel framework that seamlessly
  integrates visuospatial and linguistic domains. VisuoThink facilitates
  multimodal slow thinking by enabling progressive visual-textual reasoning and
  incorporates test-time scaling through look-ahead tree search. Extensive
  experiments demonstrate that VisuoThink significantly enhances reasoning
  capabilities via inference-time scaling, even without fine-tuning, achieving
  state-of-the-art performance in tasks involving geometry and spatial reasoning.
paper_ai_summary: VisuoThink enhances visual-verbal reasoning by combining visuospatial and linguistic domains, enabling progressive reasoning and unsupervised scaling for complex tasks.
paper_ai_keywords: Large Vision-Language Models visuospatial linguistic domains progressive visual-textual reasoning look-ahead tree search inference-time scaling geometry spatial reasoning