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Headline generation is a special type of text summarization task.
1901
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Bengio, Y., Simard, P., Frasconi, P.: Learning long-term dependencies with gradient descent is difficult. IEEE Transactions on Neural Networks 5
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Sandhaus, E.: The new york times annotated corpus ldc2008t19. dvd. Linguistic Data Consortium, Philadelphia (2008)
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Mikolov, T., Sutskever, I., Chen, K., Corrado, G., Dean, J.: Distributed representations of words and phrases and their compositionality. In Proceedings of NIPS (2013)
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Rush, A.M., Chopra, S., Weston, J.: A neural attention model for abstractive sentence summarization. In: Empirical Methods in Natural Language Processing. pp. 379–389 (2015)
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Joulin, A., Grave, E., Bojanowski, P., Mikolov, T.: Bag of tricks for efficient text classification. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers. vol. 2, pp. 427–431 (2017)
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Hayashi, Y., Yanagimoto, H.: Headline generation with recurrent neural network. In: New Trends in E-service and Smart Computing, pp. 81–96. Springer (2018)
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Kim, B., Kim, H., Kim, G.: Abstractive Summarization of Reddit Posts with Multi-level Memory Networks. In: arXiv (2018)
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Putra, J.W.G., Kobayashi, H., Shimizu, N.: Experiment on using topic sentence for neural news headline generation (2018)
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Tan, J., Wan, X., Xiao, J.: From neural sentence summarization to headline generation: a coarse-to-fine approach. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence. pp. 4109–4115. AAAI Press (2017)
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