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Comparative Study of CNN and RNN for Natural Language Processing

arXiv 1702.01923 ↗First posted 7 Feb 2017cs.CLcited by 81

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Abstract (arXiv)

Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main types of DNN architectures, are widely explored to handle various NLP tasks. CNN is supposed to be good at extracting position-invariant features and RNN at modeling units in sequence. The state of the art on many NLP tasks often switches due to the battle between CNNs and RNNs. This work is the first systematic comparison of CNN and RNN on a wide range of representative NLP tasks, aiming to give basic guidance for DNN selection.

Key facts. Cited by 81 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Feb 2017.

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Citing papers per year: 2021: 27; 2022: 13; 2023: 14; 2024: 16; 2025: 11.

81 papers.

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  2. 2021A systematic review of Hate Speech automatic detection using Natural Language Processingcited by 26
  3. 2023On the Detectability of ChatGPT Content: Benchmarking, Methodology, and Evaluation through the Lens of Academic Writingcited by 26
  4. 2022The SIGMORPHON 2022 Shared Task on Morpheme Segmentationcited by 25
  5. 2024RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processingcited by 25
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  7. 2023Zero-shot Causal Graph Extrapolation from Text via LLMscited by 15
  8. 2021HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognitioncited by 14
  9. 2021Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learningcited by 14
  10. 2021Decoding EEG Brain Activity for Multi-Modal Natural Language Processingcited by 13
  11. 2022Flipped Classroom: Effective Teaching for Time Series Forecastingcited by 11
  12. 2021Approximation Theory of Convolutional Architectures for Time Series Modellingcited by 10
38 more
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  2. 2021Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multilabel Learning Approachcited by 9
  3. 2021How May I Help You? Using Neural Text Simplification to Improve Downstream NLP Taskscited by 9
  4. 2022Quo Vadis: Hybrid Machine Learning Meta-Model based on Contextual and Behavioral Malware Representationscited by 9
  5. 2021Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectivescited by 7
  6. 2021Observation Error Covariance Specification in Dynamical Systems for Data assimilation using Recurrent Neural Networkscited by 7
  7. 2022Deep Graph Convolutional Network and LSTM based approach for predicting drug-target binding affinitycited by 7
  8. 2021Unsupervised Law Article Mining based on Deep Pre-Trained Language Representation Models with Application to the Italian Civil Codecited by 6
  9. 2022Intelligent Computing: The Latest Advances, Challenges and Futurecited by 6
  10. 2024A Large Language Model and Denoising Diffusion Framework for Targeted Design of Microstructures with Commands in Natural Languagecited by 6
  11. 2023Exposing Bias in Online Communities through Large-Scale Language Modelscited by 5
  12. 2021Jointly Modeling Aspect and Polarity for Aspect-based Sentiment Analysis in Persian Reviewscited by 4
  13. 2024Accelerating Distributed Deep Learning using Lossless Homomorphic Compressioncited by 4
  14. 2025HalluRNN: Mitigating Hallucinations via Recurrent Cross-Layer Reasoning in Large Vision-Language Modelscited by 4
  15. 2021Classifying Scientific Publications with BERT -- Is Self-Attention a Feature Selection Method?cited by 3
  16. 2021Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reductioncited by 3
  17. 2022A Survey on Automated Sarcasm Detection on Twittercited by 3
  18. 2023How to Do Machine Learning with Small Data? -- A Review from an Industrial Perspectivecited by 3
  19. 2024Explain Thyself Bully: Sentiment Aided Cyberbullying Detection with Explanationcited by 3
  20. 2024Hybrid Training for Enhanced Multi-task Generalization in Multi-agent Reinforcement Learningcited by 3
  21. 2021Computationally Efficient Wasserstein Loss for Structured Labelscited by 2
  22. 2021Literature review on vulnerability detection using NLP technologycited by 2
  23. 2021BERT Fine-Tuning for Sentiment Analysis on Indonesian Mobile Apps Reviewscited by 2
  24. 2021Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processingcited by 2
  25. 2021Lightweight Transformer in Federated Setting for Human Activity Recognitioncited by 2
  26. 2022Deep Sequence Models for Text Classification Taskscited by 2
  27. 2023Mitigating Data Scarcity for Large Language Modelscited by 2
  28. 2023Automated Reading Passage Generation with OpenAI's Large Language Modelcited by 2
  29. 2023Toward a Period-Specific Optimized Neural Network for OCR Error Correction of Historical Hebrew Textscited by 2
  30. 2024On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processescited by 2
  31. 2024VulCatch: Enhancing Binary Vulnerability Detection through CodeT5 Decompilation and KAN Advanced Feature Extractioncited by 2
  32. 2025Multi-Agent System for AI-Assisted Extraction of Narrative Arcs in TV Seriescited by 2
  33. 2025AI for Regulatory Affairs: Balancing Accuracy, Interpretability, and Computational Cost in Medical Device Classificationcited by 2
  34. 2021dictNN: A Dictionary-Enhanced CNN Approach for Classifying Hate Speech on Twittercited by 1
  35. 2021Spatio-Temporal Data Mining for Aviation Delay Predictioncited by 1
  36. 2021Machine Learning Meets Natural Language Processing -- The story so farcited by 1
  37. 2021Magnetic Field Sensing for Pedestrian and Robot Indoor Positioningcited by 1
  38. 2021CRNNTL: convolutional recurrent neural network and transfer learning for QSAR modellingcited by 1

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