ALICE++: Adversarial Training for Robust and Effective Temporal Reasoning

Lis Pereira, Fei Cheng, Masayuki Asahara, Ichiro Kobayashi


Anthology ID:
2021.paclic-1.40
Volume:
Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation
Month:
11
Year:
2021
Address:
Shanghai, China
Editors:
Kaibao Hu, Jong-Bok Kim, Chengqing Zong, Emmanuele Chersoni
Venue:
PACLIC
SIG:
Publisher:
Association for Computational Lingustics
Note:
Pages:
373–382
Language:
URL:
https://aclanthology.org/2021.paclic-1.40
DOI:
Bibkey:
Cite (ACL):
Lis Pereira, Fei Cheng, Masayuki Asahara, and Ichiro Kobayashi. 2021. ALICE++: Adversarial Training for Robust and Effective Temporal Reasoning. In Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation, pages 373–382, Shanghai, China. Association for Computational Lingustics.
Cite (Informal):
ALICE++: Adversarial Training for Robust and Effective Temporal Reasoning (Pereira et al., PACLIC 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp-22-attachments/2021.paclic-1.40.pdf
Data
CosmosQAMATRESMC-TACO