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- W1832693441 abstract "We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that a simple CNN with little hyperparameter tuning and static vectors achieves excellent results on multiple benchmarks. Learning task-specific vectors through fine-tuning offers further gains in performance. We additionally propose a simple modification to the architecture to allow for the use of both task-specific and static vectors. The CNN models discussed herein improve upon the state of the art on 4 out of 7 tasks, which include sentiment analysis and question classification." @default.
- W1832693441 created "2016-06-24" @default.
- W1832693441 creator A5045913119 @default.
- W1832693441 date "2014-01-01" @default.
- W1832693441 modified "2023-10-14" @default.
- W1832693441 title "Convolutional Neural Networks for Sentence Classification" @default.
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- W1832693441 doi "https://doi.org/10.3115/v1/d14-1181" @default.
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