62 citations · 167 across the 17 of their papers we have counts for
4 papers · 1 filter
Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers?
Minghan Li, Honglei Zhuang, Kai Hui +5
Query expansion has been widely used to improve the search results of first-stage retrievers, yet its influence on second-stage, cross-encoder rankers remains under-explored. A rec…
RD-Suite: A Benchmark for Ranking Distillation
Zhen Qin, Rolf Jagerman, Rama Pasumarthi +6
The distillation of ranking models has become an important topic in both academia and industry. In recent years, several advanced methods have been proposed to tackle this problem,…
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting
Zhen Qin, Rolf Jagerman, Kai Hui +9
Ranking documents using Large Language Models (LLMs) by directly feeding the query and candidate documents into the prompt is an interesting and practical problem. However, researc…
Query Expansion by Prompting Large Language Models
Rolf Jagerman, Honglei Zhuang, Zhen Qin +2
Query expansion is a widely used technique to improve the recall of search systems. In this paper, we propose an approach to query expansion that leverages the generative abilities…