Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task
Yilun Liu, Xiaosong Qiao, Zhanglin Wu, Su Chang, Min Zhang, Yanqing Zhao, Song Peng, Shimin Tao, Hao Yang, Ying Qin, Jiaxin Guo, Minghan Wang, Yinglu Li, Peng Li, Xiaofeng Zhao
Abstract
In this paper, we present the contribution of HW-TSC to WMT 2022 Metrics Shared Task. We propose one reference-based metric, HWTSC-EE-BERTScore*, and four referencefree metrics including HWTSC-Teacher-Sim, HWTSC-TLM, KG-BERTScore and CROSSQE. Among these metrics, HWTSC-Teacher-Sim and CROSS-QE are supervised, whereas HWTSC-EE-BERTScore*, HWTSC-TLM and KG-BERTScore are unsupervised. We use these metrics in the segment-level and systemlevel tracks. Overall, our systems achieve strong results for all language pairs on previous test sets and a new state-of-the-art in many sys-level case sets.- Anthology ID:
- 2022.wmt-1.48
- Volume:
- Proceedings of the Seventh Conference on Machine Translation (WMT)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Philipp Koehn, Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Tom Kocmi, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Marco Turchi, Marcos Zampieri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 549–557
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.48
- DOI:
- Bibkey:
- Cite (ACL):
- Yilun Liu, Xiaosong Qiao, Zhanglin Wu, Su Chang, Min Zhang, Yanqing Zhao, Song Peng, Shimin Tao, Hao Yang, Ying Qin, Jiaxin Guo, Minghan Wang, Yinglu Li, Peng Li, and Xiaofeng Zhao. 2022. Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 549–557, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task (Liu et al., WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.48.pdf
Export citation
@inproceedings{liu-etal-2022-partial,
title = "Partial Could Be Better than Whole. {HW}-{TSC} 2022 Submission for the Metrics Shared Task",
author = "Liu, Yilun and
Qiao, Xiaosong and
Wu, Zhanglin and
Chang, Su and
Zhang, Min and
Zhao, Yanqing and
Peng, Song and
Tao, Shimin and
Yang, Hao and
Qin, Ying and
Guo, Jiaxin and
Wang, Minghan and
Li, Yinglu and
Li, Peng and
Zhao, Xiaofeng",
editor = {Koehn, Philipp and
Barrault, Lo{\"\i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Freitag, Markus and
Graham, Yvette and
Grundkiewicz, Roman and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Jimeno Yepes, Antonio and
Kocmi, Tom and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Popel, Martin and
Turchi, Marco and
Zampieri, Marcos},
booktitle = "Proceedings of the Seventh Conference on Machine Translation (WMT)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wmt-1.48",
pages = "549--557",
abstract = "In this paper, we present the contribution of HW-TSC to WMT 2022 Metrics Shared Task. We propose one reference-based metric, HWTSC-EE-BERTScore*, and four referencefree metrics including HWTSC-Teacher-Sim, HWTSC-TLM, KG-BERTScore and CROSSQE. Among these metrics, HWTSC-Teacher-Sim and CROSS-QE are supervised, whereas HWTSC-EE-BERTScore*, HWTSC-TLM and KG-BERTScore are unsupervised. We use these metrics in the segment-level and systemlevel tracks. Overall, our systems achieve strong results for all language pairs on previous test sets and a new state-of-the-art in many sys-level case sets.",
}
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%0 Conference Proceedings %T Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task %A Liu, Yilun %A Qiao, Xiaosong %A Wu, Zhanglin %A Chang, Su %A Zhang, Min %A Zhao, Yanqing %A Peng, Song %A Tao, Shimin %A Yang, Hao %A Qin, Ying %A Guo, Jiaxin %A Wang, Minghan %A Li, Yinglu %A Li, Peng %A Zhao, Xiaofeng %Y Koehn, Philipp %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Jimeno Yepes, Antonio %Y Kocmi, Tom %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Popel, Martin %Y Turchi, Marco %Y Zampieri, Marcos %S Proceedings of the Seventh Conference on Machine Translation (WMT) %D 2022 %8 December %I Association for Computational Linguistics %C Abu Dhabi, United Arab Emirates (Hybrid) %F liu-etal-2022-partial %X In this paper, we present the contribution of HW-TSC to WMT 2022 Metrics Shared Task. We propose one reference-based metric, HWTSC-EE-BERTScore*, and four referencefree metrics including HWTSC-Teacher-Sim, HWTSC-TLM, KG-BERTScore and CROSSQE. Among these metrics, HWTSC-Teacher-Sim and CROSS-QE are supervised, whereas HWTSC-EE-BERTScore*, HWTSC-TLM and KG-BERTScore are unsupervised. We use these metrics in the segment-level and systemlevel tracks. Overall, our systems achieve strong results for all language pairs on previous test sets and a new state-of-the-art in many sys-level case sets. %U https://aclanthology.org/2022.wmt-1.48 %P 549-557
Markdown (Informal)
[Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task](https://aclanthology.org/2022.wmt-1.48) (Liu et al., WMT 2022)
- Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task (Liu et al., WMT 2022)
ACL
- Yilun Liu, Xiaosong Qiao, Zhanglin Wu, Su Chang, Min Zhang, Yanqing Zhao, Song Peng, Shimin Tao, Hao Yang, Ying Qin, Jiaxin Guo, Minghan Wang, Yinglu Li, Peng Li, and Xiaofeng Zhao. 2022. Partial Could Be Better than Whole. HW-TSC 2022 Submission for the Metrics Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 549–557, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.