@inproceedings{lu-poesio-2021-coreference,
title = "Coreference Resolution for the Biomedical Domain: A Survey",
author = "Lu, Pengcheng and
Poesio, Massimo",
editor = "Ogrodniczuk, Maciej and
Pradhan, Sameer and
Poesio, Massimo and
Grishina, Yulia and
Ng, Vincent",
booktitle = "Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.crac-1.2",
doi = "10.18653/v1/2021.crac-1.2",
pages = "12--23",
abstract = "Issues with coreference resolution are one of the most frequently mentioned challenges for information extraction from the biomedical literature. Thus, the biomedical genre has long been the second most researched genre for coreference resolution after the news domain, and the subject of a great deal of research for NLP in general. In recent years this interest has grown enormously leading to the development of a number of substantial datasets, of domain-specific contextual language models, and of several architectures. In this paper we review the state of-the-art of coreference in the biomedical domain with a particular attention on these most recent developments.",
}
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<abstract>Issues with coreference resolution are one of the most frequently mentioned challenges for information extraction from the biomedical literature. Thus, the biomedical genre has long been the second most researched genre for coreference resolution after the news domain, and the subject of a great deal of research for NLP in general. In recent years this interest has grown enormously leading to the development of a number of substantial datasets, of domain-specific contextual language models, and of several architectures. In this paper we review the state of-the-art of coreference in the biomedical domain with a particular attention on these most recent developments.</abstract>
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%0 Conference Proceedings
%T Coreference Resolution for the Biomedical Domain: A Survey
%A Lu, Pengcheng
%A Poesio, Massimo
%Y Ogrodniczuk, Maciej
%Y Pradhan, Sameer
%Y Poesio, Massimo
%Y Grishina, Yulia
%Y Ng, Vincent
%S Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F lu-poesio-2021-coreference
%X Issues with coreference resolution are one of the most frequently mentioned challenges for information extraction from the biomedical literature. Thus, the biomedical genre has long been the second most researched genre for coreference resolution after the news domain, and the subject of a great deal of research for NLP in general. In recent years this interest has grown enormously leading to the development of a number of substantial datasets, of domain-specific contextual language models, and of several architectures. In this paper we review the state of-the-art of coreference in the biomedical domain with a particular attention on these most recent developments.
%R 10.18653/v1/2021.crac-1.2
%U https://aclanthology.org/2021.crac-1.2
%U https://doi.org/10.18653/v1/2021.crac-1.2
%P 12-23
Markdown (Informal)
[Coreference Resolution for the Biomedical Domain: A Survey](https://aclanthology.org/2021.crac-1.2) (Lu & Poesio, CRAC 2021)
ACL