%0 Conference Paper %1 kim2014convolutional %A Kim, Yoon %D 2014 %K classification cnn nlp seminar sentence ss2018 thema thema:cnn_kim %T Convolutional Neural Networks for Sentence Classification %U http://arxiv.org/abs/1408.5882 %X 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.

@inproceedings{kim2014convolutional, 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.}, added-at = {2018-01-17T13:54:08.000+0100}, author = {Kim, Yoon}, biburl = {https://www.bibsonomy.org/bibtex/22b2e4afbc7f9c81dbc79e2a80e461f3f/schwemmlein}, description = {Convolutional Neural Networks for Sentence Classification}, interhash = {5a18dcdef0fe1455c8d7d96cee67e2b6}, intrahash = {2b2e4afbc7f9c81dbc79e2a80e461f3f}, keywords = {classification cnn nlp seminar sentence ss2018 thema thema:cnn_kim}, note = {cite arxiv:1408.5882Comment: To appear in EMNLP 2014}, timestamp = {2018-03-19T19:31:41.000+0100}, title = {Convolutional Neural Networks for Sentence Classification}, url = {http://arxiv.org/abs/1408.5882}, year = 2014 }