2 papers
cs.CR2026
Calibrating One-Round Membership Inference with Neighbors
Francesco Rita, Jie Zhang, Florian Tramèr
The state-of-the-art Membership Inference (MI) methods calibrate their signal separately for each example using reference models, auxiliary models trained to exclude the target. Th…
cs.CL2025
Do Generalisation Results Generalise?
Matteo Boglioni, Andrea Sgobbi, Gabriel Tavernini +3
A large language model's (LLM's) out-of-distribution (OOD) generalisation ability is crucial to its deployment. Previous work assessing LLMs' generalisation performance, however, t…