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The network uses Dynamic k-Max Pooling, a global pooling operation\nover linear sequences. The network handles input sentences of varying length\nand induces a feature graph over the sentence that is capable of explicitly\ncapturing short and long-range relations. The network does not rely on a parse\ntree and is easily applicable to any language. We test the DCNN in four\nexperiments: small scale binary and multi-class sentiment prediction, six-way\nquestion classification and Twitter sentiment prediction by distant\nsupervision. The network achieves excellent performance in the first three\ntasks and a greater than 25% error reduction in the last task with respect to\nthe strongest baseline.","url_abs":"http://arxiv.org/abs/1404.2188v1","url_pdf":"http://arxiv.org/pdf/1404.2188v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-convolutional-neural-network-for-modelling","repo_url":"https://github.com/Suro-One/Hyena-Hierachy","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"a-convolutional-neural-network-for-modelling","repo_url":"https://github.com/Suro-One/Hyena-Hierarchy","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"a-convolutional-neural-network-for-modelling","repo_url":"https://github.com/chojc408/Dynamic-CNN-using-Global_k_MaxPooling1D","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"a-convolutional-neural-network-for-modelling","repo_url":"https://github.com/gyanmittal/text-classification-using-char-level-embedding-with-cnn-and-keras","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"a-convolutional-neural-network-for-modelling","repo_url":"https://github.com/kinimod23/ATS_Project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"a-convolutional-neural-network-for-modelling","repo_url":"https://github.com/MindSpore-scientific/code-12/tree/main/Hyena-A-Convolutional-Neural-Network-for-Modelling-Sentences","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1404.2188","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1404.2188"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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