CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

G Zerveas, N Rekabsaz, D Cohen… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …
被引用次数：10 相关文章

CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

G Zerveas, N Rekabsaz, D Cohen, C Eickhoff - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
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 …
[PDF] health-nlp.com

[PDF][PDF] CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

G Zerveas, N Rekabsaz, D Cohen, C Eickhoff - health-nlp.com
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 …
[PDF] health-nlp.com

[PDF][PDF] CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

G Zerveas, N Rekabsaz, D Cohen, C Eickhoff - health-nlp.com
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 …

CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

G Zerveas, N Rekabsaz, D Cohen… - Proceedings of the 2022 …, 2022 - aclanthology.org
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 …