TY - GEN
T1 - Sentence Ordering with a Coherence Verifier
AU - Jia, Sainan
AU - Song, Wei
AU - Gong, Jiefu
AU - Wang, Shijin
AU - Liu, Ting
N1 - Publisher Copyright:
© 2023 Association for Computational Linguistics.
PY - 2023
Y1 - 2023
N2 - This paper presents a novel sentence ordering method by plugging a coherence verifier (COVER) into pair-wise ranking-based and sequence generation-based methods. It does not change the model parameters of the baseline, and only verifies the coherence of candidate (partial) orders produced by the baseline and reranks them in beam search. We also propose a coherence model as COVER with a novel graph formulation and a novel data construction strategy for contrastive pre-training independently of the sentence ordering task. Experimental results on four benchmarks demonstrate the effectiveness of our method with topological sorting-based and pointer network-based methods as the baselines. Detailed analyses illustrate how COVER improves the baselines and confirm the importance of its graph formulation and training strategy. Our code is available at https://github.com/SN-Jia/SO_with_CoVer.
AB - This paper presents a novel sentence ordering method by plugging a coherence verifier (COVER) into pair-wise ranking-based and sequence generation-based methods. It does not change the model parameters of the baseline, and only verifies the coherence of candidate (partial) orders produced by the baseline and reranks them in beam search. We also propose a coherence model as COVER with a novel graph formulation and a novel data construction strategy for contrastive pre-training independently of the sentence ordering task. Experimental results on four benchmarks demonstrate the effectiveness of our method with topological sorting-based and pointer network-based methods as the baselines. Detailed analyses illustrate how COVER improves the baselines and confirm the importance of its graph formulation and training strategy. Our code is available at https://github.com/SN-Jia/SO_with_CoVer.
UR - https://www.scopus.com/pages/publications/85175477545
U2 - 10.18653/v1/2023.findings-acl.592
DO - 10.18653/v1/2023.findings-acl.592
M3 - 会议稿件
AN - SCOPUS:85175477545
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 9301
EP - 9314
BT - Findings of the Association for Computational Linguistics, ACL 2023
PB - Association for Computational Linguistics (ACL)
T2 - Findings of the Association for Computational Linguistics, ACL 2023
Y2 - 9 July 2023 through 14 July 2023
ER -