The document summarizes a study that compares different deep learning models for sentence classification using the TREC dataset. It investigates convolutional neural networks, LSTM models, and combinations. Results show that architectures that retain temporal information, like LSTMs, work better than those that do not. The author proposes replacing the final fully connected layer with a linear support vector machine to improve performance.