MC-RAG: Structure-Driven Retrieval-Augmented Generation for Multi-Constraint Queries

Jul 14, 2026

A new preprint introduces MC-RAG, a structure-driven retrieval-augmented generation (RAG) system that reformulates retrieval as a subgraph matching problem over a knowledge graph. By combining semantic and structural embeddings with path-level indexing, MC-RAG aims to improve the handling of complex, multi-constraint queries, offering more interpretable and constraint-consistent retrieval and generation. The system is demonstrated with interactive examples and a demo video.

Why it matters: MC-RAG proposes a novel approach to address the challenge of constraint violations and hallucinations in RAG systems when handling complex queries, potentially improving reliability and interpretability.

Full story at: arXiv Information Retrieval ↗