이선경 박사과정 ACL 2026 Industry Track 국제 학술대회 논문 채택

18 Apr 2025

DIAL 연구실 소속 인공지능학과 이선경(박사과정, 제1저자) 학생, 이종욱(교신저자) 교수가 참여한 논문 "From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines"이 자연어처리 분야 최우수 국제 학술대회인 The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026) Industry Track에 최종 게재가 승인되었으며 오는 7월에 발표될 예정입니다.

Abstract

Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large language models. However, existing works primarily optimize for relevance while often overlooking document trustworthiness. This is critical in high-stakes domains like healthcare and finance, where relying solely on semantic relevance risks retrieving unreliable information. To address this, we propose an Authority-aware Generative Retriever (AuthGR), the first framework that incorporates authority into GenIR. AuthGR consists of three key components: (i) Multimodal Authority Scoring, which employs a vision-language model to quantify authority from textual and visual cues; (ii) a Three-stage Training Pipeline to progressively instill authority awareness into the retriever; and (iii) a Hybrid Ensemble Pipeline for robust deployment. Offline evaluations demonstrate that AuthGR successfully enhances both authority and accuracy, with our 3B model matching a 14B baseline. Crucially, large-scale online A/B tests and human evaluations conducted on the commercial web search platform confirm significant improvements in real-world user engagement and reliability.