# Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks

arXiv: https://arxiv.org/abs/1603.03827 · HTML: https://mlsanity.com/paper/1603.03827/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Mar 2016.

## Built on by (most cited first, 28 of 28)

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- [Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention](https://mlsanity.com/paper/2305.00262/) (2023)
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- [Sectioning of Biomedical Abstracts: A Sequence of Sequence Classification Task](https://mlsanity.com/paper/2201.07112/) (2022)
- [A Universality-Individuality Integration Model for Dialog Act Classification](https://mlsanity.com/paper/2204.06185/) (2022)
- [Hawk: An Industrial-strength Multi-label Document Classifier](https://mlsanity.com/paper/2301.06057/) (2023)
- [SECNN: Squeeze-and-Excitation Convolutional Neural Network for Sentence Classification](https://mlsanity.com/paper/2312.06088/) (2023)
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- [Automatic Detection of Industry Sectors in Legal Articles Using Machine Learning Approaches](https://mlsanity.com/paper/2303.05387/) (2023)
- [Multidimensional Perceptron for Efficient and Explainable Long Text Classification](https://mlsanity.com/paper/2304.01638/) (2023)
- [Machine Learning Technique Based Fake News Detection](https://mlsanity.com/paper/2309.13069/) (2023)
- [Scale-Translation Equivariant Network for Oceanic Internal Solitary Wave Localization](https://mlsanity.com/paper/2406.13060/) (2024)
- [QiBERT -- Classifying Online Conversations Messages with BERT as a Feature](https://mlsanity.com/paper/2409.05530/) (2024)
- [Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting](https://mlsanity.com/paper/2504.19021/) (2025)
- [ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model](https://mlsanity.com/paper/2507.15067/) (2025)

## Abstract (arXiv)

Recent approaches based on artificial neural networks (ANNs) have shown promising results for short-text classification. However, many short texts occur in sequences (e.g., sentences in a document or utterances in a dialog), and most existing ANN-based systems do not leverage the preceding short texts when classifying a subsequent one. In this work, we present a model based on recurrent neural networks and convolutional neural networks that incorporates the preceding short texts. Our model achieves state-of-the-art results on three different datasets for dialog act prediction.