8 papers
GreenPlanner: Practical Floorplan Layout Generation via an Energy-Aware and Function-Feasible Generative Framework
Pengyu Zeng, Yuqin Dai, Jun Yin +7
Building design directly affects human well-being and carbon emissions, yet generating spatial-functional and energy-compliant floorplans remains manual, costly, and non-scalable.…
EviNote-RAG: Enhancing RAG Models via Answer-Supportive Evidence Notes
Yuqin Dai, Guoqing Wang, Yuan Wang +13
Retrieval-Augmented Generation (RAG) has advanced open-domain question answering by incorporating external information into model reasoning. However, effectively leveraging externa…
FloorPlan-DeepSeek (FPDS): A multimodal approach to floorplan generation using vector-based next room prediction
Jun Yin, Pengyu Zeng, Jing Zhong +4
In the architectural design process, floor plan generation is inherently progressive and iterative. However, existing generative models for floor plans are predominantly end-to-end…
FloorplanMAE:A self-supervised framework for complete floorplan generation from partial inputs
Jun Yin, Jing Zhong, Pengyu Zeng +4
In the architectural design process, floorplan design is often a dynamic and iterative process. Architects progressively draw various parts of the floorplan according to their idea…
ArchiLense: A Framework for Quantitative Analysis of Architectural Styles Based on Vision Large Language Models
Jing Zhong, Jun Yin, Peilin Li +4
Architectural cultures across regions are characterized by stylistic diversity, shaped by historical, social, and technological contexts in addition to geograph-ical conditions. Un…
Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning
Yuqin Dai, Shuo Yang, Guoqing Wang +10
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating up-to-date external knowledge, yet real-world web environments present unique challenges.…