1 citations · 1 across the 4 of their papers we have counts for
4 papers
From Ranked Documents to Reliable Contexts: An Answer-Oriented Context Construct Framework for AI Search
Yunfei Zhong, Yinqiong Cai, Lixin Su +7
Traditional Web search follows a human-facing paradigm in which users inspect ranked documents and synthesize information themselves. In AI Search, retrieved documents instead serv…
Querit-Reranker: Training Compact Multilingual Rerankers via Efficient Label-Free Distribution Adaptation
Yunfei Zhong, Jun Yang, Wei Huang +7
A deployable multilingual reranker must not only generalize across languages, domains, and ranking tasks, but also remain efficient to serve as a second-stage reranker in practical…
VeriCite: Towards Reliable Citations in Retrieval-Augmented Generation via Rigorous Verification
Haosheng Qian, Yixing Fan, Jiafeng Guo +4
Retrieval-Augmented Generation (RAG) has emerged as a crucial approach for enhancing the responses of large language models (LLMs) with external knowledge sources. Despite the impr…
On the Capacity of Citation Generation by Large Language Models
Haosheng Qian, Yixing Fan, Ruqing Zhang +1
Retrieval-augmented generation (RAG) appears as a promising method to alleviate the "hallucination" problem in large language models (LLMs), since it can incorporate external trace…