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

George Zerveas; Navid Rekabsaz; D. Cohen; Carsten Eickhoff

doi:10.18653/v1/2022.emnlp-main.727

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

George Zerveas
, Navid Rekabsaz
, D. Cohen
, Carsten Eickhoff

Institute of Computational Perception

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Original language	English
Title of host publication	In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Editors	Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Pages	10626-10644
Number of pages	19
ISBN (Electronic)	9781959429401
DOIs	https://doi.org/10.18653/v1/2022.emnlp-main.727
Publication status	Published - Dec 2022

Publication series

Name	Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

Fields of science

202002 Audiovisual media
102 Computer Sciences
102001 Artificial intelligence
102003 Image processing
102015 Information systems

JKU Focus areas

Digital Transformation

Access to Document

10.18653/v1/2022.emnlp-main.727

Cite this

Zerveas, G., Rekabsaz, N., Cohen, D., & Eickhoff, C. (2022). CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. In Y. Goldberg, Z. Kozareva, & Y. Zhang (Eds.), In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 10626-10644). (Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022). https://doi.org/10.18653/v1/2022.emnlp-main.727

Zerveas, George ; Rekabsaz, Navid ; Cohen, D. et al. / CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP). editor / Yoav Goldberg ; Zornitsa Kozareva ; Yue Zhang. 2022. pp. 10626-10644 (Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022).

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title = "CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking",

author = "George Zerveas and Navid Rekabsaz and D. Cohen and Carsten Eickhoff",

year = "2022",

month = dec,

doi = "10.18653/v1/2022.emnlp-main.727",

language = "English",

series = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022",

pages = "10626--10644",

editor = "Yoav Goldberg and Zornitsa Kozareva and Yue Zhang",

booktitle = "In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP)",

}

Zerveas, G, Rekabsaz, N, Cohen, D & Eickhoff, C 2022, CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. in Y Goldberg, Z Kozareva & Y Zhang (eds), In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP). Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, pp. 10626-10644. https://doi.org/10.18653/v1/2022.emnlp-main.727

CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. / Zerveas, George; Rekabsaz, Navid; Cohen, D. et al.
In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP). ed. / Yoav Goldberg; Zornitsa Kozareva; Yue Zhang. 2022. p. 10626-10644 (Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

T1 - CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

AU - Zerveas, George

AU - Rekabsaz, Navid

AU - Cohen, D.

AU - Eickhoff, Carsten

PY - 2022/12

Y1 - 2022/12

UR - https://www.scopus.com/pages/publications/85149443216

U2 - 10.18653/v1/2022.emnlp-main.727

DO - 10.18653/v1/2022.emnlp-main.727

M3 - Conference proceedings

T3 - Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

SP - 10626

EP - 10644

BT - In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP)

A2 - Goldberg, Yoav

A2 - Kozareva, Zornitsa

A2 - Zhang, Yue

ER -

Zerveas G, Rekabsaz N, Cohen D, Eickhoff C. CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. In Goldberg Y, Kozareva Z, Zhang Y, editors, In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2022. p. 10626-10644. (Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022). doi: 10.18653/v1/2022.emnlp-main.727

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

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