Adversarial Robustness on In- and Out-Distribution Improves Explainability. - Maximilian Augustin; Alexander Meinke; Matthias Hein 001 (ECCV (26), 2020)

Towards neural networks that provably know when they don't know. - Alexander Meinke; Matthias Hein 001 (ICLR, 2020)

Certifiably Adversarially Robust Detection of Out-of-Distribution Data. - Julian Bitterwolf; Alexander Meinke; Matthias Hein 001 (NeurIPS, 2020)

Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data. - Julian Bitterwolf; Alexander Meinke; Matthias Hein 001 (CoRR, 2020)

Provably Robust Detection of Out-of-distribution Data (almost) for free. - Alexander Meinke; Julian Bitterwolf; Matthias Hein 001 (CoRR, 2021)

Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities. - Julian Bitterwolf; Alexander Meinke; Maximilian Augustin; Matthias Hein 001 (ICML, 2022)

Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free. - Alexander Meinke; Julian Bitterwolf; Matthias Hein 001 (NeurIPS, 2022)

Improving Fairness and Cybersecurity in the Artificial Intelligence Act. - Gabriele Carovano; Alexander Meinke (EWAF, 2023)

Tell, don't show: Declarative facts influence how LLMs generalize. - Alexander Meinke; Owain Evans (CoRR, 2023)

Robust Out-of-Distribution Detection in Deep Classifiers. - Alexander Meinke (2023)

Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs. - Rudolf Laine; Bilal Chughtai; Jan Betley; Kaivalya Hariharan; Mikita Balesni; Jérémy Scheurer; Marius Hobbhahn; Alexander Meinke; Owain Evans (NeurIPS, 2024)

Towards evaluations-based safety cases for AI scheming. - Mikita Balesni; Marius Hobbhahn; David Lindner; Alexander Meinke; Tomek Korbak; Joshua Clymer; Buck Shlegeris; Jérémy Scheurer; Charlotte Stix; Rusheb Shah; Nicholas Goldowsky-Dill; Dan Braun; et al. (CoRR, 2024)

Frontier Models are Capable of In-context Scheming. - Alexander Meinke; Bronson Schoen; Jérémy Scheurer; Mikita Balesni; Rusheb Shah; Marius Hobbhahn (CoRR, 2024)

Multi-Agent Risks from Advanced AI. - Lewis Hammond; Alan Chan; Jesse Clifton; Jason Hoelscher-Obermaier; Akbir Khan; Euan McLean; Chandler Smith; Wolfram Barfuss; Jakob N. Foerster; Tomas Gavenciak; The Anh Han; Edward Hughes 001; et al. (CoRR, 2025)

Stress Testing Deliberative Alignment for Anti-Scheming Training. - Bronson Schoen; Evgenia Nitishinskaya; Mikita Balesni; Axel Højmark; Felix Hofstätter; Jérémy Scheurer; Alexander Meinke; Jason Wolfe; Teun van der Weij; Alex Lloyd; Nicholas Goldowsky-Dill; Angela Fan; et al. (CoRR, 2025)