Publications [#346721] of Lawrence Carin

Papers Published

1. Gan, Z; Pu, Y; Henao, R; Li, C; He, X; Carin, L, Learning generic sentence representations using convolutional neural networks, EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings (January, 2017), pp. 2390-2400, ISBN 9781945626838 [doi]
   (last updated on 2024/12/31)

   Abstract:
   We propose a new encoder-decoder approach to learn distributed sentence representations that are applicable to multiple purposes. The model is learned by using a convolutional neural network as an encoder to map an input sentence into a continuous vector, and using a long short-term memory recurrent neural network as a decoder. Several tasks are considered, including sentence reconstruction and future sentence prediction. Further, a hierarchical encoder-decoder model is proposed to encode a sentence to predict multiple future sentences. By training our models on a large collection of novels, we obtain a highly generic convolutional sentence encoder that performs well in practice. Experimental results on several benchmark datasets, and across a broad range of applications, demonstrate the superiority of the proposed model over competing methods.