Deep Learning on Graphs for Natural Language Processing

North American Chapter of the Association for Computational Linguistics (NAACL)

Abstract

This tutorial of Deep Learning on Graphs for Natural Language Processing (DLG4NLP) is timely for the computational linguistics community, and covers relevant and interesting topics, including automatic graph construction for NLP, graph representation learning for NLP, various advanced GNN based models (e.g., graph2seq, graph2tree, and graph2graph) for NLP, and the applications of GNNs in various NLP tasks (e.g., machine translation, natural language generation, information extraction and semantic parsing). The intended audiences for this tutorial mainly include graduate students and researchers in the field of Natural Language Processing and industry professionals who want to know how the state-of-the-art deep learning on graphs techniques can help solve important yet challenging Natural Language Processing problems.

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