33 citations · 172 across the 29 of their papers we have counts for
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cs.CL2022★ 6 cited
LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval
Kai Zhang, Chongyang Tao, Tao Shen +4
Retrieval models based on dense representations in semantic space have become an indispensable branch for first-stage retrieval. These retrievers benefit from surging advances in r…
cs.CL2022★ 3 cited
MORE: A Metric Learning Based Framework for Open-domain Relation Extraction
Yutong Wang, Renze Lou, Kai Zhang +2
Open relation extraction (OpenRE) is the task of extracting relation schemes from open-domain corpora. Most existing OpenRE methods either do not fully benefit from high-quality la…
cs.IR2022★ 7 cited
UnifieR: A Unified Retriever for Large-Scale Retrieval
Tao Shen, Xiubo Geng, Chongyang Tao +4
Large-scale retrieval is to recall relevant documents from a huge collection given a query. It relies on representation learning to embed documents and queries into a common semant…