AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation

1 code implementation • NeurIPS 2023 • Björn Deiseroth, Mayukh Deb, Samuel Weinbach, Manuel Brack, Patrick Schramowski, Kristian Kersting

Generative transformer models have become increasingly complex, with large numbers of parameters and the ability to process multiple input modalities.

DORA: Exploring Outlier Representations in Deep Neural Networks

1 code implementation • 9 Jun 2022 • Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M. -C. Höhne

Deep Neural Networks (DNNs) excel at learning complex abstractions within their internal representations.

Decision Making