Papers by Ernesto William De Luca

1 papers
HOTTER: Hierarchical Optimal Topic Transport with Explanatory Context Representations (2021.findings-emnlp)

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Challenge: Natural language processing (NLP) is often the backbone of today’s systems for user interactions, information retrieval and others.
Approach: They propose an extension to a specific emerging hybrid document distance metric which combines topic models and word embeddings.
Outcome: The proposed method is competitive on public datasets and the language model BERT is used for a document categorization task.

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