Benchmarking Middle-Trained Language Models for Neural Search-Reference-Cited by-同舟云学术

Benchmarking Middle-Trained Language Models for Neural Search

Published:2023-07-18 Issue: Volume: Page:
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Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Déjean Hervé¹^ORCID,Clinchant Stephane¹^ORCID,Lassance Carlos¹^ORCID,Lupart Simon¹^ORCID,Formal Thibault¹^ORCID

Affiliation:

1. Naver Labs Europe, Meylan, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591956

Reference37 articles.

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5. Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2019 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding . In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 4171--4186. https://doi.org/10. 18653/v1/N19--1423 10.18653/v1 Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 4171--4186. https://doi.org/10.18653/v1/N19--1423

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