{"work":{"id":"993684ab-aaf8-4590-bb77-5d7aec85dffc","openalex_id":null,"doi":null,"arxiv_id":"1408.5882","raw_key":null,"title":"Convolutional Neural Networks for Sentence Classification","authors":null,"authors_text":"Yoon Kim","year":2014,"venue":"cs.CL","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.","external_url":"https://arxiv.org/abs/1408.5882","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-05-25T19:01:09.035612+00:00","pith_arxiv_id":"1408.5882","created_at":"2026-05-11T00:20:54.796231+00:00","updated_at":"2026-05-25T19:01:09.035612+00:00","title_quality_ok":true,"display_title":"Convolutional neural networks for sentence classification","render_title":"Convolutional neural networks for sentence classification"},"hub":{"state":{"work_id":"993684ab-aaf8-4590-bb77-5d7aec85dffc","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":16,"external_cited_by_count":null,"distinct_field_count":10,"first_pith_cited_at":"2019-06-21T05:29:40+00:00","last_pith_cited_at":"2026-05-11T12:08:41+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-06-02T21:55:08.858690+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":2},{"context_role":"baseline","n":1}],"polarity_counts":[{"context_polarity":"background","n":2},{"context_polarity":"baseline","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}