一作SIGIR 2026Poster· Information Retrieval (Industry)
Learning to Trust: Dynamic Utilization of Retrieval-Augmented Generation for E-commerce Search Relevance
Tingqiao Xu · Shaowei Yao (Taobao & · Chenhe Dong (Taobao & · Chenhe Dong (Taobao & · Zerui Huang (Taobao & · Chenhe Dong (Taobao & · Xingxian Liu (Taobao & · Zerui Huang (Taobao & · Shengjie Sun (Taobao & · Chenhe Dong (Taobao & · Shengjie Sun (Taobao & · Xingxian Liu (Taobao & · Shengjie Sun (Taobao & · Bo Zheng (Taobao & · Shengjie Sun (Taobao &
摘要
Accurately estimating query-item relevance is vital for e-commerce ranking and conversion. While Large Language Models (LLMs) excel at reasoning, they often lack specialized knowledge required for long-tail or fast-evolving queries, necessitating Retrieval-Augmented Generation (RAG). However, pro...