Multi-path Based Self-adaptive Cross-lingual Summarization

Author:

Bao ZhongtianORCID,Wang JunORCID,Yang ZhengluORCID

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Shree Akshaya, A.T., Shankaran, S., Thrupthi, H., Mamatha, H.: Natural language processing based cross lingual summarization. In: Proceedings of 6th ICOEI, pp. 1825–1829 (2022)

2. Aumiller, D., Chouhan, A., Gertz, M.: EUR-Lex-Sum: a multi-and cross-lingual dataset for long-form summarization in the legal domain. In: Proceedings of 2022 EMNLP, pp. 7626–7639 (2022)

3. Bai, Y., et al.: Unifying cross-lingual summarization and machine translation with compression rate. In: Proceedings of 45th SIGIR, pp. 1087–1097 (2022)

4. Bhattacharjee, A., Hasan, T., Ahmad, W.U., Li, Y.F., bin Kang, Y., Shahriyar, R.: CrossSum: beyond English-centric cross-lingual abstractive text summarization for 1500+ language pairs. CoRR (2021)

5. Cao, Y., Liu, H., Wan, X.: Jointly learning to align and summarize for neural cross-lingual summarization. In: Proceedings of 58th ACL, pp. 6220–6231 (2020)

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