svjan5/GNNs-for-NLP
Tutorial: Graph Neural Networks for Natural Language Processing at EMNLP 2019 and CODS-COMAD 2020
This project provides code examples and materials for understanding how Graph Neural Networks (GNNs) can be applied to language-related problems. It takes in text data and demonstrates how to process it using GNNs to gain insights for tasks like identifying relationships between entities, generating word embeddings, or even time-stamping documents. This is for researchers and practitioners in natural language processing who want to explore advanced deep learning techniques for text analysis.
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Use this if you are an NLP researcher or data scientist looking for practical examples and a foundational understanding of applying Graph Neural Networks to various language processing tasks.
Not ideal if you are looking for a plug-and-play solution for a specific NLP problem without delving into the underlying graph neural network architectures.
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Mar 24, 2023
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