VULCAN: Tool-Augmented Multi-Agent 3D Object Arrangement
Published:Dec 26, 2025 19:22
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of applying Multimodal Large Language Models (MLLMs) to complex 3D scene manipulation. It tackles the limitations of MLLMs in 3D object arrangement by introducing an MCP-based API for robust interaction, augmenting scene understanding with visual tools for feedback, and employing a multi-agent framework for iterative updates and error handling. The work is significant because it bridges a gap in MLLM application and demonstrates improved performance on complex 3D tasks.
Key Takeaways
- •Addresses the limitations of MLLMs in 3D object arrangement.
- •Introduces an MCP-based API for robust interaction.
- •Augments scene understanding with visual tools.
- •Employs a multi-agent framework for iterative updates and error handling.
- •Demonstrates improved performance on complex 3D tasks.
Reference
“The paper's core contribution is the development of a system that uses a multi-agent framework with specialized tools to improve 3D object arrangement using MLLMs.”