NLP804: Deep Learning for Natural Language Generation
TB = Textbook or Required reading 
REF = Reference or supplemental reading
| Type | Title |
eBook |
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Call Number | ||
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D. Foster, Generative Deep Learning, 2nd ed. Sebastopol, CA, USA: O'Reilly Media, 2022. | Oreilly. | Yes | |||
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L. Deng and Y. Liu, Deep Learning in Natural Language Processing. Singapore: Springer, 2018. | Springer | Yes | QA76.9.N38 D364 2018 | ||
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E. Reiter and R. Dale, Building Natural Language Generation Systems. Cambridge, UK: Cambridge University Press, 2000. | Cambridge Core | Yes | QA76.9.N38 R45 2006 | ||
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K. McKeown, Text Generation. Cambridge, UK: Cambridge University Press, 1992. | Cambridge Core | Yes | P302 .M392 1992 | ||
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Ferreira, Thiago Castro, et al. Neural data-to-text generation: A comparison between pipeline and end-to-end architectures. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019. | Open Access | NA | ||
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van der Lee, Chris, Emiel Krahmer, and Sander Wubben. "Automated learning of templates for data-to-text generation: comparing rule-based, statistical and neural methods." Proceedings of the 11th International Conference on Natural Language Generation. 2018. |
ACM | NA | ||
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Puduppully, Ratish, Li Dong, and Mirella Lapata. "Data-to-text Generation with Entity Modeling." Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019. |
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NA | ||
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Puduppully, Ratish, Li Dong, and Mirella Lapata. "Data-to-text generation with content selection and planning." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33. 2019. |
ADM | NA | ||
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Nie, Feng, et al. "A simple recipe towards reducing hallucination in neural surface realisation." Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019. |
Open Access | NA | ||
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Reed, Lena, Shereen Oraby, and Marilyn Walker. "Can Neural Generators for Dialogue Learn Sentence Planning and Discourse Structuring?." Proceedings of the 11th International Conference on Natural Language Generation. 2018. |
Open Access | NA | ||
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Wiseman, Sam, Stuart M. Shieber, and Alexander M. Rush. "Learning Neural Templates for Text Generation." Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2018. |
NA | |||
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Perez-Beltrachini, Laura, and Mirella Lapata. "Bootstrapping Generators from Noisy Data." Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018. |
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NA | ||
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Marcheggiani, Diego, and Laura Perez-Beltrachini. "Deep Graph Convolutional Encoders for Structured Data to Text Generation." Proceedings of the 11th International Conference on Natural Language Generation. 2018. |
NA | |||
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Balakrishnan, Anusha, et al. Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019. |
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NA | ||
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Moryossef, Amit, Yoav Goldberg, and Ido Dagan. Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019. |
NA | |||
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Ippolito, Daphne, et al. Automatic detection of generated text is easiest when humans are fooled.Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020. |
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NA | ||
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Koncel-Kedziorski, Rik, et al. Text Generation from Knowledge Graphs with Graph Transformers.Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019. | NA | |||
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Gehrmann, Sebastian, et al. End-to-End Content and Plan Selection for Data-to-Text Generation. Proceedings of the 11th International Conference on Natural Language Generation. 2018. | NA |