{"slug": "agentic-designer-progressive-multi-agent-collaboration-for-structure-aware", "title": "Agentic Designer: Progressive Multi-Agent Collaboration for Structure-Aware Interior Layout Generation", "summary": "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.", "body_md": "arXiv:2607.20866v1 Announce Type: new\nAbstract: 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.", "url": "https://wpnews.pro/news/agentic-designer-progressive-multi-agent-collaboration-for-structure-aware", "canonical_source": "https://arxiv.org/abs/2607.20866", "published_at": "2026-07-24 04:00:00+00:00", "updated_at": "2026-07-24 04:28:38.104821+00:00", "lang": "en", "topics": ["artificial-intelligence", "generative-ai", "ai-agents"], "entities": ["Agentic Designer", "InStruct", "Generator", "Evaluator", "Refiner", "Progressive Consensus Mechanism"], "alternates": {"html": "https://wpnews.pro/news/agentic-designer-progressive-multi-agent-collaboration-for-structure-aware", "markdown": "https://wpnews.pro/news/agentic-designer-progressive-multi-agent-collaboration-for-structure-aware.md", "text": "https://wpnews.pro/news/agentic-designer-progressive-multi-agent-collaboration-for-structure-aware.txt", "jsonld": "https://wpnews.pro/news/agentic-designer-progressive-multi-agent-collaboration-for-structure-aware.jsonld"}}