299 citations · 370 across the 9 of their papers we have counts for
3 papers · 1 filter
Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighbors
George Zerveas, Navid Rekabsaz, Carsten Eickhoff
Sparse annotation poses persistent challenges to training dense retrieval models; for example, it distorts the training signal when unlabeled relevant documents are used spuriously…
CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking
George Zerveas, Navid Rekabsaz, Daniel Cohen +1
Contrastive learning has been the dominant approach to training dense retrieval models. In this work, we investigate the impact of ranking context - an often overlooked aspect of l…
Brown University at TREC Deep Learning 2019
George Zerveas, Ruochen Zhang, Leila Kim +1
This paper describes Brown University's submission to the TREC 2019 Deep Learning track. We followed a 2-phase method for producing a ranking of passages for a given input query: I…