17 citations · 32 across the 6 of their papers we have counts for
17 papers
Multi-Vector Retrieval as Sparse Alignment
Yujie Qian, Jinhyuk Lee, Sai Meher Karthik Duddu +5
Multi-vector retrieval models improve over single-vector dual encoders on many information retrieval tasks. In this paper, we cast the multi-vector retrieval problem as sparse alig…
Bridging the Training-Inference Gap for Dense Phrase Retrieval
Gyuwan Kim, Jinhyuk Lee, Barlas Oguz +4
Building dense retrievers requires a series of standard procedures, including training and validating neural models and creating indexes for efficient search. However, these proced…
Phrase Retrieval Learns Passage Retrieval, Too
Jinhyuk Lee, Alexander Wettig, Danqi Chen
Dense retrieval methods have shown great promise over sparse retrieval methods in a range of NLP problems. Among them, dense phrase retrieval-the most fine-grained retrieval unit-i…
Can Language Models be Biomedical Knowledge Bases?
Mujeen Sung, Jinhyuk Lee, Sean Yi +3
Pre-trained language models (LMs) have become ubiquitous in solving various natural language processing (NLP) tasks. There has been increasing interest in what knowledge these LMs…
Learning Dense Representations of Phrases at Scale
Jinhyuk Lee, Mujeen Sung, Jaewoo Kang +1
Open-domain question answering can be reformulated as a phrase retrieval problem, without the need for processing documents on-demand during inference (Seo et al., 2019). However,…
Answering Questions on COVID-19 in Real-Time
Jinhyuk Lee, Sean S. Yi, Minbyul Jeong +5
The recent outbreak of the novel coronavirus is wreaking havoc on the world and researchers are struggling to effectively combat it. One reason why the fight is difficult is due to…