Tobias Lorenz

LLM panels running the Delphi protocol achieve strong calibration (r=0.87–0.95) against benchmark ground truth and align closely with human expert panels, reducing elicitation time from months to minutes.

MIBP-Cert uses mixed-integer bilinear programming to compute sound, deterministic robustness bounds during training, handling complex threat models including discrete and continuous data perturbations.

3DCertify, the first verifier for point cloud models, certifies robustness against a wide range of semantic 3D transformations for both classification and part segmentation.

A GAN that synthesizes CNN features conditioned on class-level semantic information, enabling effective generalized zero-shot learning without labeled examples of unseen classes.