Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. - Arsenii Ashukha; Alexander Lyzhov; Dmitry Molchanov; Dmitry P. Vetrov (ICLR, 2020)

Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. - Alexander Lyzhov; Yuliya Molchanova; Arsenii Ashukha; Dmitry Molchanov; Dmitry P. Vetrov (UAI, 2020)

Normative Disagreement as a Challenge for Cooperative AI. - Julian Stastny; Maxime Riché; Alexander Lyzhov; Johannes Treutlein; Allan Dafoe; Jesse Clifton (CoRR, 2021)

Inverse Scaling: When Bigger Isn't Better. - Ian R. McKenzie; Alexander Lyzhov; Michael Pieler; Alicia Parrish; Aaron Mueller; Ameya Prabhu; Euan McLean; Aaron Kirtland; Alexis Ross; Alisa Liu; Andrew Gritsevskiy; Daniel Wurgaft; et al. (Trans. Mach. Learn. Res., 2023)

Steering Without Side Effects: Improving Post-Deployment Control of Language Models. - Asa Cooper Stickland; Alexander Lyzhov; Jacob Pfau; Salsabila Mahdi; Samuel R. Bowman (CoRR, 2024)

HalluciNot: Hallucination Detection Through Context and Common Knowledge Verification. - Bibek Paudel; Alexander Lyzhov; Preetam Joshi; Puneet Anand (CoRR, 2025)