mlsanityData to 7 Oct 2026

Deep Learning applied to NLP

arXiv 1703.03091 ↗First posted 9 Mar 2017cs.CLcited by 11

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Abstract (arXiv)

Convolutional Neural Network (CNNs) are typically associated with Computer Vision. CNNs are responsible for major breakthroughs in Image Classification and are the core of most Computer Vision systems today. More recently CNNs have been applied to problems in Natural Language Processing and gotten some interesting results. In this paper, we will try to explain the basics of CNNs, its different variations and how they have been applied to NLP.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Mar 2017.

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Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 5.

11 papers.

  1. 2022From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Datacited by 38
  2. 2024Graph Neural Networks for Financial Fraud Detection: A Reviewcited by 24
  3. 2024Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapescited by 10
  4. 2021TI-Capsule: Capsule Network for Stock Exchange Predictioncited by 4
  5. 2024Not Just Change the Labels, Learn the Features: Watermarking Deep Neural Networks with Multi-View Datacited by 2
  6. 2024Computational Approaches to Arabic-English Code-Switchingcited by 1
  7. 2022ABG: A Multi-Party Mixed Protocol Framework for Privacy-Preserving Cooperative Learningcited by 0
  8. 2022Deep neural networks for fine-grained surveillance of overdose mortalitycited by 0
  9. 2023On the Identification of the Energy related Issues from the App Reviewscited by 0
  10. 2023Feature Extraction Using Deep Generative Models for Bangla Text Classification on a New Comprehensive Datasetcited by 0
  11. 2024Cross-Modality Clustering-based Self-Labeling for Multimodal Data Classificationcited by 0