5 citations · 5 across the 1 of their papers we have counts for
3 papers
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA
Patryk Marszałek, Klaudia Bałazy, Jacek Tabor +1
Low-Rank Adaptation (LoRA) enables parameter-efficient fine-tuning of large language models by decomposing weight updates into low-rank matrices, significantly reducing storage and…
Direction is what you need: Improving Word Embedding Compression in Large Language Models
Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret +2
The adoption of Transformer-based models in natural language processing (NLP) has led to great success using a massive number of parameters. However, due to deployment constraints…
Finding the Optimal Network Depth in Classification Tasks
Bartosz Wójcik, Maciej Wołczyk, Klaudia Bałazy +1
We develop a fast end-to-end method for training lightweight neural networks using multiple classifier heads. By allowing the model to determine the importance of each head and rew…