Using the output embedding to improve language models
Original
Press, O. and Wolf, L. (2016) · 2016
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Neural machine translation of rare words with subword units
Sennrich, R., Haddow, B., and Birch, A. (2016) · 2016
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Minimum risk training for neural machine translation
Shen, S., Cheng, Y., He, Z., He, W., Wu, H., Sun, M., and Liu, Y. (2016) · 2016
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Rethinking the inception architecture for computer vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., and Wojna, Z. (2016) · 2016
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DyNet: The Dynamic Neural Network Toolkit
Original
Neubig, G., Dyer, C., Goldberg, Y., Matthews, A., Ammar, W., Anastasopoulos, A., Ballesteros, M., Chiang, D., Clothiaux, D., Cohn, T., Duh, K., Faruqui, M., Gan, C., Garrette, D., Ji, Y., Kong, L., Kuncoro, A., Kumar, G., Malaviya, C., Michel, P., Oda, Y., Richardson, M., Saphra, N., Swayamdipta, S., and Yin, P. (2017) · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I. (2017) · 2017
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Very deep convolutional networks for end-to-end speech recognition
Zhang, Y., Chan, W., and Jaitly, N. (2017) · 2017
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Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the ”speaking rosetta” JSALT 2017 workshop
Scharenborg, O., Besacier, L., Black, A., Hasegawa-Johnson, M., Metze, F., Neubig, G., Stuker, S., Godard, P., Muller, M., Ondel, L., Palaskar, S., Arthur, P., Ciannella, F., Du, M., Larsen, E., Merkx, D., Riad, R., Wang, L., and Dupoux, E. (2018) · 2018
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