# Convolutional Neural Networks for Sentence Classification

**Authors:** Yoon Kim  
**arXiv:** [1408.5882](https://arxiv.org/abs/1408.5882)  
**Date:** 2014-08-25  
**Summary page:** https://www.summarizepaper.com/fr/paper/1408.5882v2/

## Abstract

We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that a simple CNN with little hyperparameter tuning and static vectors achieves excellent results on multiple benchmarks. Learning task-specific vectors through fine-tuning offers further gains in performance. We additionally propose a simple modification to the architecture to allow for the use of both task-specific and static vectors. The CNN models discussed herein improve upon the state of the art on 4 out of 7 tasks, which include sentiment analysis and question classification.