AAAI2026

RefLens: End-to-End Evidence-Grounded Citation Verification with LLM Agents

Seunghoo Lee, JuneHyoung Kwon, Jooweon Choi, JungMin Yun, Seunguk Yu, Yoonji Lee, Jinhee Jang, YoungBin Kim

Abstract

Accurate citation is critical, yet error rates remain high across scientific literature. We present RefLens, an end-to-end system that automates citation verification from PDF parsing to interactive report generation. Unlike summary- or embedding-based approaches, RefLens performs evidence-grounded verification by extracting verbatim spans from original sources and displaying citation-level cards and a paper-level dashboard. In a 35-participant study, users rated value (M=4.34), trust (M=4.15), and usability (M=4.19) highly, with strong adoption intention (M=4.28).