LSTMs Exploit Linguistic Attributes of Data
Rep4NLP@ACL, pp. 180-186, 2018.
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Abstract:
While recurrent neural networks have found success in a variety of natural language processing applications, they are general models of sequential data. We investigate how the properties of natural language data affect an LSTMu0027s ability to learn a nonlinguistic task: recalling elements from its input. We find that models trained on na...More
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