Using Captum to Explain Generative Language Models
Captum is a comprehensive library for model explainability in PyTorch,
offering a range of methods from the interpretability literature to enhance
users' understanding of PyTorch models. In this paper, we introduce new
features in Captum that are specifically designed to analyze the behavior of
generative language models. We provide an overview of the available
functionalities and example applications of their potential for understanding
learned associations within generative language models.
6577da0390df9d85fb4cde66
Vivek Miglani
admin_assigned
2023-12-12T08:53:05.848Z
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/avatars/5fd80bd830bcc2279be36497116da561.svg
Vivek Miglani
user
vivekmig
6577da0390df9d85fb4cde67
Aobo Yang
admin_assigned
2023-12-12T08:53:15.213Z
64c85fe8c96a10fa85a14910
/avatars/7dfd9cc9127f0af5a4ed87fe11985d71.svg
Aobo Yang
user
aobo-y
6577da0390df9d85fb4cde68
Aram H. Markosyan
admin_assigned
2023-12-12T08:53:23.623Z
63fe54211193ba2c229bd74a
/avatars/14c7cc8b9ebde8d6d4f16e578e311396.svg
Aram Markosyan
user
armarkos
6577da0390df9d85fb4cde69
Diego Garcia-Olano
admin_assigned
2023-12-12T08:53:29.597Z
61166b0bc47d4efbfa8be996
/avatars/3c5da13cab6bf4876ac40f2df062ad84.svg
Diego Garcia-Olano
user
diegoolano
6577da0390df9d85fb4cde6a
Narine Kokhlikyan
Using Captum to Explain Generative Language Models
Captum is a comprehensive library for model explainability in PyTorch,
offering a range of methods from the interpretability literature to enhance
users' understanding of PyTorch models. In this paper, we introduce new
features in Captum that are specifically designed to analyze the behavior of
generative language models. We provide an overview of the available
functionalities and example applications of their potential for understanding
learned associations within generative language models.
Captum introduces new features for analyzing the behavior of generative language models in PyTorch, enhancing model explainability.
model explainability generative language models interpretability literature