Finding the Optimal Network Depth in Classification Tasks. - Bartosz Wójcik; Maciej Wolczyk; Klaudia Balazy; Jacek Tabor (ECML/PKDD (3), 2020)

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. - Maciej Wolczyk; Bartosz Wójcik; Klaudia Balazy; Igor T. Podolak; Jacek Tabor; Marek Smieja; Tomasz Trzcinski (NeurIPS, 2021)

Direction is what you need: Improving Word Embedding Compression in Large Language Models. - Klaudia Balazy; Mohammadreza Banaei; Rémi Lebret; Jacek Tabor; Karl Aberer (RepL4NLP@ACL-IJCNLP, 2021)

Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models. - Mohammadreza Banaei; Klaudia Balazy; Artur Kasymov; Rémi Lebret; Jacek Tabor; Karl Aberer (EACL (Findings), 2023)

Step by Step Loss Goes Very Far: Multi-Step Quantization for Adversarial Text Attacks. - Piotr Gainski; Klaudia Balazy (EACL, 2023)

r-softmax: Generalized Softmax with Controllable Sparsity Rate. - Klaudia Balazy; Lukasz Struski; Marek Smieja; Jacek Tabor (ICCS (2), 2023)

Exploiting Transformer Activation Sparsity with Dynamic Inference. - Mikolaj Piórczynski; Filip Szatkowski; Klaudia Balazy; Bartosz Wójcik (CoRR, 2023)

Zero time waste in pre-trained early exit neural networks. - Bartosz Wójcik; Marcin Przewiezlikowski; Filip Szatkowski; Maciej Wolczyk; Klaudia Balazy; Bartlomiej Krzepkowski; Igor T. Podolak; Jacek Tabor; Marek Smieja; Tomasz Trzcinski (Neural Networks, 2023)

LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters. - Klaudia Balazy; Mohammadreza Banaei; Karl Aberer; Jacek Tabor (CoRR, 2024)

A Deeper Look into the Limitations of Early-Exit Architectures for Single and Multi-label Classification. - Klaudia Balazy; Julian J. McAuley; Jacek Tabor (ICCS (1), 2025)

Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA. - Patryk Marszalek; Klaudia Balazy; Jacek Tabor; Tomasz Kusmierczyk (CoRR, 2025)