README
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AI & ML interests
We build interpretable models and AI systems that can reliably explain their reasoning, and are easy to audit, steer, and understand.
juliusadebayo
updated
a
Space
about 1 year ago
andreasmadsen
authored
a
paper
over 1 year ago
andreasmadsen
authored
6
papers
almost 2 years ago
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining
Paper
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2110.08412
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Published
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1
Faithfulness Measurable Masked Language Models
Paper
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2310.07819
•
Published
Measuring Arithmetic Extrapolation Performance
Paper
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1910.01888
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Published
Neural Arithmetic Units
Paper
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2001.05016
•
Published
Post-hoc Interpretability for Neural NLP: A Survey
Paper
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2108.04840
•
Published
Can Large Language Models Explain Themselves?
Paper
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2401.07927
•
Published
•
4