Graph-enhanced multi-answer summarization under question-driven guidance

Author:

Li Bing,Yang Peng,Hu Zhongjian,Sun Yuankang,Yi Meng

Funder

the National Natural Science Foundation of China

the Consulting Project of Chinese Academy of Engineering under Grant

the National Social Science Fund of China under Grant

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Reference56 articles.

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2. Zhang J, Tan J, Wan X (2018) Adapting neural single-document summarization model for abstractive multi-document summarization: a pilot study. In: Proceedings of the 11th International Conference on Natural Language Generation, pp 381–390. https://doi.org/10.18653/v1/w18-6545

3. Baumel T, Eyal M, Elhadad M (2018) Query focused abstractive summarization: incorporating query relevance, multi-document coverage, and summary length constraints into seq2seq models. CoRR arXiv:abs/1801.07704

4. Lebanoff L, Song K, Liu F (2018) Adapting the neural encoder-decoder framework from single to multi-document summarization. In: EMNLP, pp 4131–4141. https://doi.org/10.18653/v1/d18-1446

5. Cohan A, Dernoncourt F, Kim DS, Bui T, Kim S, Chang W, Goharian N (2018) A discourse-aware attention model for abstractive summarization of long documents. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, pp 615–621. https://doi.org/10.18653/v1/n18-2097

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