How about Time? Probing a Multilingual Language Model for Temporal Relations

Tommaso Caselli; Irene Dini; Felice Dell’Orletta

How about Time? Probing a Multilingual Language Model for Temporal Relations

Tommaso Caselli, Irene Dini, Felice Dell’Orletta

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Abstract

This paper presents a comprehensive set of probing experiments using a multilingual language model, XLM-R, for temporal relation classification between events in four languages. Results show an advantage of contextualized embeddings over static ones and a detrimen- tal role of sentence level embeddings. While obtaining competitive results against state-of-the-art systems, our probes indicate a lack of suitable encoded information to properly address this task.

Anthology ID:: 2022.coling-1.283
Volume:: Proceedings of the 29th International Conference on Computational Linguistics
Month:: October
Year:: 2022
Address:: Gyeongju, Republic of Korea
Editors:: Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
Venue:: COLING
SIG:
Publisher:: International Committee on Computational Linguistics
Note:
Pages:: 3197–3209
Language:
URL:: https://aclanthology.org/2022.coling-1.283/
DOI:
Bibkey:
Cite (ACL):: Tommaso Caselli, Irene Dini, and Felice Dell’Orletta. 2022. How about Time? Probing a Multilingual Language Model for Temporal Relations. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3197–3209, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):: How about Time? Probing a Multilingual Language Model for Temporal Relations (Caselli et al., COLING 2022)
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PDF:: https://aclanthology.org/2022.coling-1.283.pdf
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@inproceedings{caselli-etal-2022-time,
    title = "How about Time? Probing a Multilingual Language Model for Temporal Relations",
    author = "Caselli, Tommaso  and
      Dini, Irene  and
      Dell{'}Orletta, Felice",
    editor = "Calzolari, Nicoletta  and
      Huang, Chu-Ren  and
      Kim, Hansaem  and
      Pustejovsky, James  and
      Wanner, Leo  and
      Choi, Key-Sun  and
      Ryu, Pum-Mo  and
      Chen, Hsin-Hsi  and
      Donatelli, Lucia  and
      Ji, Heng  and
      Kurohashi, Sadao  and
      Paggio, Patrizia  and
      Xue, Nianwen  and
      Kim, Seokhwan  and
      Hahm, Younggyun  and
      He, Zhong  and
      Lee, Tony Kyungil  and
      Santus, Enrico  and
      Bond, Francis  and
      Na, Seung-Hoon",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2022.coling-1.283/",
    pages = "3197--3209",
    abstract = "This paper presents a comprehensive set of probing experiments using a multilingual language model, XLM-R, for temporal relation classification between events in four languages. Results show an advantage of contextualized embeddings over static ones and a detrimen- tal role of sentence level embeddings. While obtaining competitive results against state-of-the-art systems, our probes indicate a lack of suitable encoded information to properly address this task."
}

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%0 Conference Proceedings
%T How about Time? Probing a Multilingual Language Model for Temporal Relations
%A Caselli, Tommaso
%A Dini, Irene
%A Dell’Orletta, Felice
%Y Calzolari, Nicoletta
%Y Huang, Chu-Ren
%Y Kim, Hansaem
%Y Pustejovsky, James
%Y Wanner, Leo
%Y Choi, Key-Sun
%Y Ryu, Pum-Mo
%Y Chen, Hsin-Hsi
%Y Donatelli, Lucia
%Y Ji, Heng
%Y Kurohashi, Sadao
%Y Paggio, Patrizia
%Y Xue, Nianwen
%Y Kim, Seokhwan
%Y Hahm, Younggyun
%Y He, Zhong
%Y Lee, Tony Kyungil
%Y Santus, Enrico
%Y Bond, Francis
%Y Na, Seung-Hoon
%S Proceedings of the 29th International Conference on Computational Linguistics
%D 2022
%8 October
%I International Committee on Computational Linguistics
%C Gyeongju, Republic of Korea
%F caselli-etal-2022-time
%X This paper presents a comprehensive set of probing experiments using a multilingual language model, XLM-R, for temporal relation classification between events in four languages. Results show an advantage of contextualized embeddings over static ones and a detrimen- tal role of sentence level embeddings. While obtaining competitive results against state-of-the-art systems, our probes indicate a lack of suitable encoded information to properly address this task.
%U https://aclanthology.org/2022.coling-1.283/
%P 3197-3209

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Markdown (Informal)

[How about Time? Probing a Multilingual Language Model for Temporal Relations](https://aclanthology.org/2022.coling-1.283/) (Caselli et al., COLING 2022)

How about Time? Probing a Multilingual Language Model for Temporal Relations (Caselli et al., COLING 2022)

ACL

Tommaso Caselli, Irene Dini, and Felice Dell’Orletta. 2022. How about Time? Probing a Multilingual Language Model for Temporal Relations. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3197–3209, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.