{"type":"ScholarlyArticle","title":"MC-RAG System: A Structure-Driven RAG System for Multi-Constraint Queries","authors":[{"name":"Xiao Zhang","slug":"xiao-zhang","given":"Xiao","family":"Zhang","affiliation":""},{"name":"Yang Wan","slug":"yang-wan","given":"Yang","family":"Wan","affiliation":""},{"name":"Yi Li","slug":"yi-li","given":"Yi","family":"Li","affiliation":""},{"name":"Miao Xie","slug":"miao-xie","given":"Miao","family":"Xie","affiliation":""},{"name":"Chunli Lv","slug":"chunli-lv","given":"Chunli","family":"Lv","affiliation":""}],"abstract":"Retrieval-Augmented Generation (RAG) systems are widely adopted in question answering, yet they often fail to satisfy complex multi-constraint queries, leading to constraint violations, factual inconsistencies, or hallucinations. We present Structure-Driven RAG System for Multi-Constraint Queries(MC-RAG), a structure-driven RAG system that reformulates retrieval as a subgraph matching problem over a knowledge graph. By integrating semantic and structural embeddings with path-level indexing, MC-RAG performs interpretable, structure-aware, and constraint-consistent retrieval and generation. During the demonstration, participants can input medical or encyclopedic multi-constraint queries, visualize how the system parses constraints, performs structural matching, and generates answers, thereby experiencing an end-to-end, interactive, and explainable RAG pipeline. \r\nA demo video is available at https://youtu.be/J8kahzmAnu0.","doi":"10.24963/ijcai.2026/1002","url":"https://ijcai.org/proceedings/2026/1002","pdf":"https://ijcai.org/proceedings/2026/1002.pdf","markdown":"https://ijcai.org/proceedings/2026/1002.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/1002","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Demo Track","track":"Demo Track","number":1002,"pages":{"first":8555,"last":8559},"keywords":["AI: Natural Language Processing","AI: Knowledge Representation and Reasoning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}