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May, 2018
LSTMs Exploit Linguistic Attributes of Data
LSTMs Exploit Linguistic Attributes of Data
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Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, Noah A. Smith
TL;DR
研究如何通过自然语言数据训练LSTM模型，并发现这种数据能够帮助LSTM模型更好地记忆并回忆输入的令牌，同时LSTM也会通过某些神经元来计算输入的时间步数。
Abstract
While
recurrent neural networks
have found success in a variety of
natural language processing
applications, they are general models of
sequentia
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