Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks. - Luca Scimeca; Alexander Rubinstein 002; Armand Mihai Nicolicioiu; Damien Teney; Yoshua Bengio (CoRR, 2023)

Trustworthy Machine Learning. - Bálint Mucsányi; Michael Kirchhof; Elisa Nguyen; Alexander Rubinstein 002; Seong Joon Oh (CoRR, 2023)

Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models. - Luca Scimeca; Alexander Rubinstein 002; Damien Teney; Seong Joon Oh; Armand Mihai Nicolicioiu; Yoshua Bengio (CoRR, 2023)

Studying Large Language Model Behaviors Under Realistic Knowledge Conflicts. - Evgenii Kortukov; Alexander Rubinstein 002; Elisa Nguyen; Seong Joon Oh (CoRR, 2024)

Scalable Ensemble Diversification for OOD Generalization and Detection. - Alexander Rubinstein 002; Luca Scimeca; Damien Teney; Seong Joon Oh (CoRR, 2024)

Do Deep Neural Network Solutions Form a Star Domain? - Ankit Sonthalia; Alexander Rubinstein 002; Ehsan Abbasnejad; Seong Joon Oh (ICLR, 2025)

Are We Done with Object-Centric Learning? - Alexander Rubinstein 002; Ameya Prabhu; Matthias Bethge; Seong Joon Oh (CoRR, 2025)