On the Detection of Anomalous or Out-of-Distribution Data in Vision Models Using Statistical Techniques. - Laura O'Mahony; David JP O'Sullivan; Nikola S. Nikolov (AICV, 2023)

Disentangling Neuron Representations with Concept Vectors. - Laura O'Mahony; Vincent Andrearczyk; Henning Müller; Mara Graziani (CVPR Workshops, 2023)

Uncovering Unique Concept Vectors through Latent Space Decomposition. - Mara Graziani; Laura O'Mahony; An-Phi Nguyen; Henning Müller; Vincent Andrearczyk (Trans. Mach. Learn. Res., 2023)

Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning. - Shivalika Singh; Freddie Vargus; Daniel D'souza; Börje Karlsson 001; Abinaya Mahendiran; Wei-Yin Ko; Herumb Shandilya; Jay Patel; Deividas Mataciunas; Laura O'Mahony; Mike Zhang; Ramith Hettiarachchi; et al. (ACL (1), 2024)

Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning. - Shivalika Singh; Freddie Vargus; Daniel D'souza; Börje F. Karlsson; Abinaya Mahendiran; Wei-Yin Ko; Herumb Shandilya; Jay Patel; Deividas Mataciunas; Laura O'Mahony; Mike Zhang; Ramith Hettiarachchi; et al. (CoRR, 2024)

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models. - Alex Havrilla; Andrew Dai 001; Laura O'Mahony; Koen Oostermeijer; Vera Zisler; Alon Albalak; Fabrizio Milo; Sharath Chandra Raparthy; Kanishk Gandhi; Baber Abbasi; Duy Phung; Maia Iyer; et al. (CoRR, 2024)

Towards Utilising a Range of Neural Activations for Comprehending Representational Associations. - Laura O'Mahony; Nikola S. Nikolov; David J. P. O'Sullivan (WACV, 2025)