4 papers
UniSGR: Unified Framework for Semantic ID Generation and Ranking
Jiawei Sun, Jun Yang, Ziyue Guo +4
Recommendation systems play a pivotal role in modern e-commerce platforms. While generative retrieval has emerged as a promising paradigm for alleviating the limitations of multi-s…
Querit-Reranker: Training Compact Multilingual Rerankers via Efficient Label-Free Distribution Adaptation
Yunfei Zhong, Jun Yang, Wei Huang +7
Deployable multilingual rerankers must generalize across languages, domains, and target ranking tasks while remaining efficient enough for second-stage reranking. However, adapting…
Towards AI Search Paradigm
Yuchen Li, Hengyi Cai, Rui Kong +20
In this paper, we introduce the AI Search Paradigm, a comprehensive blueprint for next-generation search systems capable of emulating human information processing and decision-maki…
Reason to Retrieve: Enhancing Query Understanding through Decomposition and Interpretation
Yunfei Zhong, Jun Yang, Yixing Fan +4
Query understanding (QU) aims to accurately infer user intent to improve document retrieval. It plays a vital role in modern search engines. While large language models (LLMs) have…