4 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
MA4DIV: Multi-Agent Reinforcement Learning for Search Result Diversification
Yiqun Chen, Jiaxin Mao, Yi Zhang +7
Search result diversification (SRD), which aims to ensure that documents in a ranking list cover a broad range of subtopics, is a significant and widely studied problem in Informat…
Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction
Canjia Li, Xiaoyang Wang, Dongdong Li +6
Search engine plays a crucial role in satisfying users' diverse information needs. Recently, Pretrained Language Models (PLMs) based text ranking models have achieved huge success…
PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation
Lianshang Cai, Linhao Zhang, Dehong Ma +6
Pre-trained language models have become a crucial part of ranking systems and achieved very impressive effects recently. To maintain high performance while keeping efficient comput…
CPS-MEBR: Click Feedback-Aware Web Page Summarization for Multi-Embedding-Based Retrieval
Wenbiao Li, Pan Tang, Zhengfan Wu +7
Embedding-based retrieval (EBR) is a technique to use embeddings to represent query and document, and then convert the retrieval problem into a nearest neighbor search problem in t…
Approximated Doubly Robust Search Relevance Estimation
Lixin Zou, Changying Hao, Hengyi Cai +6
Extracting query-document relevance from the sparse, biased clickthrough log is among the most fundamental tasks in the web search system. Prior art mainly learns a relevance judgm…