gianluigilopardo/anchors_text_theory
Code for the paper "A Sea of Words: An In-Depth Analysis of Anchors for Text Data", AISTATS 2023
This project helps machine learning researchers understand how "Anchors" work as a method for explaining text-based AI models. It takes in text data and trained AI models, then produces explanations and analyses of which parts of the text are most critical for a model's decisions. This is designed for researchers focused on the interpretability and explainability of natural language processing (NLP) models.
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Use this if you are a machine learning researcher studying how text-based AI models make decisions and want to rigorously evaluate the 'Anchors' explainability technique.
Not ideal if you are an end-user simply looking to get explanations from your text AI models without deep theoretical analysis.
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Python
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Last pushed
Oct 26, 2024
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