Showing cs.CLShow all
3 papers · 1 filter
cs.CL2026
Powerful Training-Free Membership Inference Against Autoregressive Language Models
David IliÄ, David StanojeviÄ, 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…
cs.CL2026
Learning the Signature of Memorization in Autoregressive Language Models
David IliÄ, Kostadin Cvejoski, David StanojeviÄ +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…
cs.CL2024
Evidence of interrelated cognitive-like capabilities in large language models: Indications of artificial general intelligence or achievement?
David IliÄ, 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…