參考文獻 |
1] Asghar, N., Poupart, P., Hoey, J., Jiang, X., and Mou, L. Affective neural response
generation. In 40th European Conference on Information Retrieval (ECIR 2018) (France,
2018).
[2] Bahdanau, D., Cho, K., and Bengio, Y. A neural conversational model. In International
Conference on Learning Representations (San Diego, California, 2014).
[3] Bahdanau, D., Cho, K., and Bengio, Y. A hierarchical latent variable encoder-decoder
model for generating dialogues. In Association for the Advancement of Artificial Intelligence
(AAAI-17) (San Francisco, California, 2017).
[4] Choi, Y., Choi, M., Kim, M., Ha, J.-W., Kim, S., and Choo, J. Stargan: Unified
generative adversarial networks for multi-domain image-to-image translation. In Conference
on Computer Vision and Pattern Recognition (CVPR) (Salt Lake City, Utah, 2018).
[5] Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. Bert: Pre-training of deep bidi-
rectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).
[6] Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D.,
Ozair, S., Courville, A., and Bengio, Y. Generative adversarial nets. In Neural Infor-
mation Processing System (NIPS-16) (2016).
[7] Hochreiter Sepp, S. J. Long short-term memory. Neural Computation (November 15,
1997), 1735{1780.
[8] Kingma, D. P., and Ba, J. L. Adam: A method for stochastic optimization. In International
Conference on Learning Representations (ICLR) (2015).
[9] Lin, C.-Y. Rouge: A package for automatic evaluation of summaries. In Proc. ACL workshop
on Text Summarization Branches Out (2004), p. 10.
[10] Martin Arjovsky, L. B. Towards principled methods for training generative adversarial
networks. In Proc. of ICLR (2017).
[11] Mikolov, T., Chen, K., Corrado, G., and Dean, J. Efficient estimation of word
representations in vector space. In Proceedings of the International Conference on Learning
Representations (ICLR) (2013).
[12] Papineni, K., Roukos, S., Ward, T., and Wei-JingZhu. Bleu: a method for automatic
evaluation of machine translation. In Proceedings of the 40th Annual Meeting on Association
for Computational Linguistics (Philadelphia, Pennsylvania, 2002).
[13] Pestian JP, Matykiewicz P, L.-G. M. S. B. U. O. W. J. C. K. H. J. B. C. Sentiment
analysis of suicide notes: A shared task. Biomed Inform Insights (2012), 3{6.
[14] Peters, M. E., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., and
Zettlemoyer, L. Deep contextualized word representations. In Proc. of NAACL (2018).
[15] Piotr Bojanowski, Edouard Grave, A. J. T. M. Enriching word vectors with subword
information. In Transactions of the Association for Computational Linguistics (2017).
[16] Serban, I. V., Sordoni, A., Bengio, Y., Courville, A., and Pineau, J. Building end-
to-end dialogue systems using generative hierarchical neural network models. In Proceedings
of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (Phoenix, Arizona,
2016).
[17] Shang, L., Lu, Z., and Li, H. Neural responding machine for short-text conversation. In
The 2015 Conference of the Association for Computational Linguistics (2015).
[18] Sutskever, I., Vinyals, O., and Le, Q. V. Sequence to sequence learning with neural net-
works. In Proceedings of the 27th International Conference on Neural Information Processing
Systems (Montreal Canada, December 08 - 13, 2014), NIPS.
[19] Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N.,
Kaiser, L., and Polosukhin, I. Attention is all you need. In 31st Conference on Neural
Information Processing System (Long Beach, California, 2017).
[20] Vinyals, O., and Le, Q. V. A neural conversational model. In Proceedings of the 31st
International Conference on Machine Learning (Lille, France, 2014).
[21] Wang, K., and Wan, X. Sentigan: Generating sentimental texts via mixture adversarial
networks. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial
Intelligence (IJCAI) (2018).
[22] Xiaohe Li, Jiaqing Liu, W. Z. X. W. Y. Z., and Dou, Z. Rucir at ntcir-14 stc-13 task. In
Proceedings of the 14th NTCIR Conference on Evaluation of Information Access Technologies
(Tokyo, Japan, 2019).
[23] Yangyang Zhou, Zheng Liu, X. K. Y. W., and Ren, F. Tkuim at ntcir-14 stc-3 cecg
task. In Proceedings of the 14th NTCIR Conference on Evaluation of Information Access
Technologies (Tokyo, Japan, 2019).
[24] Yangyang Zhou, Zheng Liu, X. K. Y. W., and Ren, F. Tua1 at the ntcir-14 stc-3
task. In Proceedings of the 14th NTCIR Conference on Evaluation of Information Access
Technologies (Tokyo, Japan, 2019).
[25] Yu, L., Zhang, W., JunWang, and Yu, Y. Distributed representations of words and
phrases and their compositionality. In Proceedings of the 26th International Conference on
Neural Information Processing Systems (Lake Tahoe, Nevada, 2013).
[26] Yu, L., Zhang, W., JunWang, and Yu, Y. Seqgan: Sequence generative adversarial
nets with policy gradient. In Proceedings of the Thirty-First AAAI Conference on Artificial
Intelligence (AAAI-17) (San Francisco, California, 2017).
[27] Yu, L., Zhang, W., JunWang, and Yu, Y. Long text generation via adversarialtraining
with leaked information. In Association for the Advancement of Artificial Intelligence (AAAI-
18) (New Orleans, Louisiana, 2018).
[28] Zhou, H., Huang, M., Zhang, T., Zhu, X., and Liu, B. Emotional chatting machine:
Emotional conversation generation with internal and external memory. In Association for the
Advancement of Artificial Intelligence (AAAI-18) (2018).
[29] Zhu, J.-Y., Park, T., Isola, P., and Efros, A. A. Unpaired image-to-image transla-
tion using cycle-consistent adversarial networks. In The IEEE International Conference on
Computer Vision (ICCV) (Venice, Italy, 2017). |