Agentic Designer: Progressive Multi-Agent Collaboration for Structure-Aware Interior Layout Generation

Researchers propose Agentic Designer, a multi-agent framework that generates interior furniture layouts by iteratively verifying geometric constraints, outperforming state-of-the-art methods in structural adherence and functional coherence. The framework coordinates three specialized agents—Generator, Evaluator, and Refiner—through a Progressive Consensus Mechanism to prevent error accumulation. To support this work, the team established InStruct, a benchmark with over 18,000 parametrically annotated samples and structure-centric metrics.

arXiv:2607.20866v1 Announce Type: new Abstract: Generating realistic interior furniture layouts that strictly adhere to architectural constraints e.g., walls, doors, and windows remains a fundamental challenge in automated spatial design. Existing approaches, primarily based on one-shot generation using diffusion models or Large Language Models LLMs , lack explicit mechanisms for intermediate geometric constraint verification, often resulting in structural collisions and functionally infeasible arrangements under complex room constraints. To address these challenges, we propose Agentic Designer, a progressive, multi-agent framework that formulates structure-aware interior layout generation as an iterative and constraint-verified decision process. By decomposing layout synthesis into modular stages of proposal, verification, and adjustment, the framework coordinates three specialized agents, a Generator, an Evaluator, and a Refiner, through a Progressive Consensus Mechanism. This mechanism enforces stepwise geometric validation and correction before each placement is committed, thereby preventing error accumulation. To facilitate this structure-aware paradigm and standardize evaluation, we establish InStruct, a comprehensive benchmark that integrates a dataset comprising over 18,000 high-quality, parametrically annotated samples with a novel suite of structure-centric metrics. Extensive quantitative evaluations, qualitative analyses, and user studies show that Agentic Designer significantly outperforms state-of-the-art methods, demonstrating substantial improvements in strict structural adherence and functional design coherence.