Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Graph Neural Networks for Natural Language Processing

Conference Conference Slides

The repository contains code examples for GNN-for-NLP tutorial at EMNLP 2019 and CODS-COMAD 2020.

Slides can be downloaded from here.

Dependencies

  • Compatible with PyTorch 1.x, TensorFlow 1.x and Python 3.x.
  • Dependencies can be installed using requirements.txt.

TensorFlow Examples:

  • tf_gcn.py contains simplified implementation of first-order approximation of GCN model proposed by Kipf et. al. (2016)
  • Extensions of the same implementation for different problems:

PyTorch Examples:

  • pytorch_gcn.py is pytorch equivalent of tf_gcn.py implemented using pytorch-geometric.
  • Several other examples are available here.

Additional Resources:

Citation:

@inproceedings{vashishth-etal-2019-graph,
    title = "Graph-based Deep Learning in Natural Language Processing",
    author = "Vashishth, Shikhar  and
      Yadati, Naganand  and
      Talukdar, Partha",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): Tutorial Abstracts",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    abstract = "This tutorial aims to introduce recent advances in graph-based deep learning techniques such as Graph Convolutional Networks (GCNs) for Natural Language Processing (NLP). It provides a brief introduction to deep learning methods on non-Euclidean domains such as graphs and justifies their relevance in NLP. It then covers recent advances in applying graph-based deep learning methods for various NLP tasks, such as semantic role labeling, machine translation, relationship extraction, and many more.",
}

About

Tutorial: Graph Neural Networks for Natural Language Processing at EMNLP 2019 and CODS-COMAD 2020

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages