Papers with deep learning text classifiers

1 papers
FIND: Human-in-the-Loop Debugging Deep Text Classifiers (2020.emnlp-main)

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Challenge: Existing models are limited in the number of available datasets and lack the necessary tools to improve them.
Approach: They propose a framework which enables humans to debug deep learning text classifiers by disabling irrelevant hidden features.
Outcome: Experiments show that using FIND, humans can improve CNN text classifiers trained on different types of imperfect datasets.

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