Search Results for author: Lenka Tětková

Found 7 papers, 2 papers with code

How Redundant Is the Transformer Stack in Speech Representation Models?

no code implementations10 Sep 2024 Teresa Dorszewski, Albert Kjøller Jacobsen, Lenka Tětková, Lars Kai Hansen

Our findings reveal a block-like structure of high similarity, suggesting two main processing steps and significant redundancy of layers.

Knowledge Distillation Speaker Identification +2

Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks

no code implementations10 Sep 2024 Teresa Dorszewski, Lenka Tětková, Lorenz Linhardt, Lars Kai Hansen

Understanding how neural networks align with human cognitive processes is a crucial step toward developing more interpretable and reliable AI systems.

Convexity-based Pruning of Speech Representation Models

no code implementations16 Aug 2024 Teresa Dorszewski, Lenka Tětková, Lars Kai Hansen

Recent work has shown that there is significant redundancy in the transformer models for NLP and massive layer pruning is feasible (Sajjad et al., 2023).

Keyword Spotting Self-Supervised Learning +1

Knowledge graphs for empirical concept retrieval

1 code implementation10 Apr 2024 Lenka Tětková, Teresa Karen Scheidt, Maria Mandrup Fogh, Ellen Marie Gaunby Jørgensen, Finn Årup Nielsen, Lars Kai Hansen

Concept-based explainable AI is promising as a tool to improve the understanding of complex models at the premises of a given user, viz.\ as a tool for personalized explainability.

General Knowledge Knowledge Graphs +1

Robustness of Visual Explanations to Common Data Augmentation

1 code implementation18 Apr 2023 Lenka Tětková, Lars Kai Hansen

As the use of deep neural networks continues to grow, understanding their behaviour has become more crucial than ever.

Data Augmentation

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