PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs

Jul 10, 2026

PolyUQuest is a retrieval-augmented generation (RAG) framework that models web pages as heterogeneous graphs, preserving HTML structure and entity relations. It uses a two-tier router to select among three retrieval modes and provides fully verifiable answers with source citations. Evaluated on a university website dataset, PolyUQuest outperforms existing RAG systems in answer correctness, coverage, and faithfulness, while using fewer LLM tokens.

Why it matters: This work addresses a key limitation of current RAG systems by leveraging structural and semantic signals from web pages for more accurate and verifiable question answering.

Full story at: arXiv AI/ML ↗