mlsanityData to 14 Oct 2026

CoRe3D: Collaborative Reasoning as a Foundation for 3D Intelligence

arXiv 2512.12768 ↗First posted 14 Dec 2025cs.CV cs.AI cs.LGcited by 10

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

Abstract (arXiv)

Recent advances in large multimodal models suggest that explicit reasoning mechanisms play a critical role in improving model reliability, interpretability, and cross-modal alignment. While such reasoning-centric approaches have been proven effective in language and vision tasks, their extension to 3D remains underdeveloped. CoRe3D introduces a unified 3D understanding and generation reasoning framework that jointly operates over semantic and spatial abstractions, enabling high-level intent inferred from language to directly guide low-level 3D content formation. Central to this design is a spatially grounded reasoning representation that decomposes 3D latent space into localized regions, allowing the model to reason over geometry in a compositional and procedural manner. By tightly coupling semantic chain-of-thought inference with structured spatial reasoning, CoRe3D produces 3D outputs that exhibit strong local consistency and faithful alignment with linguistic descriptions.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 90 of its 112 references that are in the map. First posted on arXiv 14 Dec 2025.

Builds on

90 of 112 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding2 Jun
  2. 2025R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization17 Mar
  3. 2025Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models9 Mar
  4. 2024ShapeLLM: Universal 3D Object Understanding for Embodied Interaction27 Feb
  5. 2023LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning30 Nov
  6. 2023ShapeGPT: 3D Shape Generation with A Unified Multi-modal Language Model29 Nov

Other references · 84

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  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  3. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
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38 more
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50 most cited of 84 All 84 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 10.

10 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Flame3D: Zero-shot Compositional Reasoning of 3D Scenes with Agentic Language Models
  2. 2025Think with 3D: Geometric Imagination Grounded Spatial Reasoning from Limited Views
  3. 2026GeoAnchor: Collaborative Reasoning via Latent Decomposition for 3D Spatial Understanding
  4. 2025SURPRISE3D: A Dataset for Spatial Understanding and Reasoning in Complex 3D Scenes
  5. 2026GraFT: A Training-Free Framework for Spatial Reasoning in Multimodal Large Language Models via 3D Scene Graphs
  6. 2026Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering
  7. 2026Disentangling 3D Modeling from Spatial Reasoning
  8. 2026Thinking in Structures: Evaluating Spatial Intelligence in Constraint-Governed Spaces