3 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.IR2023★ 2 cited
PaRaDe: Passage Ranking using Demonstrations with Large Language Models
Andrew Drozdov, Honglei Zhuang, Zhuyun Dai +8
Recent studies show that large language models (LLMs) can be instructed to effectively perform zero-shot passage re-ranking, in which the results of a first stage retrieval method,…
cs.IR2023★ 1 cited
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,…
cs.IR2023★ 3 cited
How Does Generative Retrieval Scale to Millions of Passages?
Ronak Pradeep, Kai Hui, Jai Gupta +5
Popularized by the Differentiable Search Index, the emerging paradigm of generative retrieval re-frames the classic information retrieval problem into a sequence-to-sequence modeli…