13 citations · 13 across the 6 of their papers we have counts for
6 papers
An X-ray and optical spectral study of the changing-look narrow-line Seyfert 1 2MASX J0413-0050
A. Vietri, A. Tortosa, D. Ilić +12
Active galactic nuclei (AGN) showing dramatic spectral and flux variations, either due to changes in the accretion rate (changing-state, CS-AGN) of the supermassive black hole or i…
Learning the Signature of Memorization in Autoregressive Language Models
David Ilić, Kostadin Cvejoski, David Stanojević +1
All prior membership inference attacks for fine-tuned language models use hand-crafted heuristics (e.g., loss thresholding, Min-K\%, reference calibration), each bounded by the des…
AGILE: an end-to-end Rubin-LSST simulation of AGNs, galaxies, and stars I. Software description and first data release
A. Viitanen, A. Bongiorno, I. Saccheo +37
Contemporary large-scale surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid present an unprecedented discovery potential for studying A…
Protecting Private Code in IDE Autocomplete using Differential Privacy
Evgeny Grigorenko, David Stanojević, David Ilić +2
Modern Integrated Development Environments (IDEs) increasingly leverage Large Language Models (LLMs) to provide advanced features like code autocomplete. While powerful, training t…
Powerful Training-Free Membership Inference Against Autoregressive Language Models
David Ilić, David Stanojević, Kostadin Cvejoski
Fine-tuned language models pose significant privacy risks, as they may memorize and expose sensitive information from their training data. Membership inference attacks (MIAs) provi…
Evidence of interrelated cognitive-like capabilities in large language models: Indications of artificial general intelligence or achievement?
David Ilić, Gilles E. Gignac
Large language models (LLMs) are advanced artificial intelligence (AI) systems that can perform a variety of tasks commonly found in human intelligence tests, such as defining word…