Correct Metadata for
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)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.283.pdf
- Code
- irenedini/tlink_probing
Export citation
@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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<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.</abstract>
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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
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.