mlsanityData to 7 Oct 2026

Deep Learning Based Text Classification: A Comprehensive Review

arXiv 2004.03705 ↗First posted 6 Apr 2020cs.CL cs.LG stat.MLcited by 140

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Abstract (arXiv)

Deep learning based models have surpassed classical machine learning based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this paper, we provide a comprehensive review of more than 150 deep learning based models for text classification developed in recent years, and discuss their technical contributions, similarities, and strengths. We also provide a summary of more than 40 popular datasets widely used for text classification. Finally, we provide a quantitative analysis of the performance of different deep learning models on popular benchmarks, and discuss future research directions.

Key facts. Cited by 140 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Apr 2020.

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Citing papers per year: 2021: 31; 2022: 42; 2023: 43; 2024: 18; 2025: 6.

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  1. 2023Dataset Distillation: A Comprehensive Reviewcited by 126
  2. 2021A Survey on Data Augmentation for Text Classificationcited by 111
  3. 2021An Empirical Survey of Data Augmentation for Limited Data Learning in NLPcited by 101
  4. 2022Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environmentscited by 57
  5. 2023A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagramcited by 55
  6. 2023Active Learning Principles for In-Context Learning with Large Language Modelscited by 53
  7. 2022LAMP: Extracting Text from Gradients with Language Model Priorscited by 52
  8. 2022Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approachescited by 39
  9. 2023Large Language Models Are Zero-Shot Text Classifierscited by 35
  10. 2021UNIREX: A Unified Learning Framework for Language Model Rationale Extractioncited by 32
  11. 2022Efficient Classification of Long Documents Using Transformerscited by 30
  12. 2022Metaphors in Pre-Trained Language Models: Probing and Generalization Across Datasets and Languagescited by 30
38 more
  1. 2021The Surprising Performance of Simple Baselines for Misinformation Detectioncited by 27
  2. 2022One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Codecited by 26
  3. 2023Rationalization for Explainable NLP: A Surveycited by 22
  4. 2023High-Throughput Vector Similarity Search in Knowledge Graphscited by 19
  5. 2022A Unified Understanding of Deep NLP Models for Text Classificationcited by 18
  6. 2021Bag-of-Words vs. Graph vs. Sequence in Text Classification: Questioning the Necessity of Text-Graphs and the Surprising Strength of a Wide MLPcited by 17
  7. 2021WikiContradiction: Detecting Self-Contradiction Articles on Wikipediacited by 17
  8. 2022Defending against the Label-flipping Attack in Federated Learningcited by 16
  9. 2024A Survey on Large Language Models from General Purpose to Medical Applications: Datasets, Methodologies, and Evaluationscited by 16
  10. 2023Graph Neural Networks for Text Classification: A Surveycited by 15
  11. 2021Multimodal Fake News Detectioncited by 14
  12. 2024Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awarenesscited by 14
  13. 2023Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Modelscited by 13
  14. 2022FL-Defender: Combating Targeted Attacks in Federated Learningcited by 12
  15. 2023A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysiscited by 12
  16. 2024CTINexus: Automatic Cyber Threat Intelligence Knowledge Graph Construction Using Large Language Modelscited by 12
  17. 2022Improving Short Text Classification With Augmented Data Using GPT-3cited by 11
  18. 2022MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusioncited by 10
  19. 2024Development of Skip Connection in Deep Neural Networks for Computer Vision and Medical Image Analysis: A Surveycited by 10
  20. 2022Automatic Analysis of Available Source Code of Top Artificial Intelligence Conference Paperscited by 9
  21. 2023Zero-Shot Learning for Requirements Classification: An Exploratory Studycited by 9
  22. 2022Extending Logic Explained Networks to Text Classificationcited by 8
  23. 2023Deep Prompt Tuning for Graph Transformerscited by 8
  24. 2021SupCL-Seq: Supervised Contrastive Learning for Downstream Optimized Sequence Representationscited by 7
  25. 2022Hierarchical Neural Network Approaches for Long Document Classificationcited by 7
  26. 2022Precise Single-stage Detectorcited by 7
  27. 2023Representation biases in sentence transformerscited by 7
  28. 2024An Empirical Study on Capability of Large Language Models in Understanding Code Semanticscited by 7
  29. 2024Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Textcited by 7
  30. 2021Natural Language Understanding for Argumentative Dialogue Systems in the Opinion Building Domaincited by 6
  31. 2021Personalized Benchmarking with the Ludwig Benchmarking Toolkitcited by 6
  32. 2022A Review on Text-Based Emotion Detection -- Techniques, Applications, Datasets, and Future Directionscited by 6
  33. 2023A Glimpse in ChatGPT Capabilities and its impact for AI researchcited by 6
  34. 2023Recent Advances in Hierarchical Multi-label Text Classification: A Surveycited by 6
  35. 2025MicroNN: An On-device Disk-resident Updatable Vector Databasecited by 6
  36. 2021Self-supervised Regularization for Text Classificationcited by 5
  37. 2021An Ensemble of Pre-trained Transformer Models For Imbalanced Multiclass Malware Classificationcited by 5
  38. 2022TextConvoNet:A Convolutional Neural Network based Architecture for Text Classificationcited by 5

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