Baader, Maximilian

20 publications

ICML 2025 A Unified Approach to Routing and Cascading for LLMs Jasper Dekoninck, Maximilian Baader, Martin Vechev

ICLRW 2025 A Unified Approach to Routing and Cascading for LLMs Jasper Dekoninck, Maximilian Baader, Martin Vechev

ICML 2025 BaxBench: Can LLMs Generate Correct and Secure Backends? Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanović, Jingxuan He, Martin Vechev

ICLRW 2025 BaxBench: Can LLMs Generate Correct and Secure Backends? Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanović, Jingxuan He, Martin Vechev

TMLR 2025 Certified Robustness to Data Poisoning in Gradient-Based Training Philip Sosnin, Mark Niklas Mueller, Maximilian Baader, Calvin Tsay, Matthew Robert Wicker

ICLR 2025 GRAIN: Exact Graph Reconstruction from Gradients Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar Iliev Dimitrov, Martin Vechev

TMLR 2025 Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations Stefan Balauca, Mark Niklas Mueller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin Vechev

ICLR 2025 Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation Jasper Dekoninck, Maximilian Baader, Martin Vechev

ICLR 2025 Ward: Provable RAG Dataset Inference via LLM Watermarks Nikola Jovanović, Robin Staab, Maximilian Baader, Martin Vechev

NeurIPS 2024 DAGER: Exact Gradient Inversion for Large Language Models Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev

ICLR 2024 Expressivity of ReLU-Networks Under Convex Relaxations Maximilian Baader, Mark Niklas Mueller, Yuhao Mao, Martin Vechev

NeurIPS 2024 SPEAR: Exact Gradient Inversion of Batches in Federated Learning Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev

ECCV 2022 Latent Space Smoothing for Individually Fair Representations Momchil Peychev, Anian Ruoss, Mislav Balunović, Maximilian Baader, Martin Vechev

TMLR 2022 On the Paradox of Certified Training Nikola Jovanović, Mislav Balunovic, Maximilian Baader, Martin Vechev

TMLR 2022 The Fundamental Limits of Neural Networks for Interval Certified Robustness Matthew B Mirman, Maximilian Baader, Martin Vechev

AAAI 2021 Efficient Certification of Spatial Robustness Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev

ICML 2021 Scalable Certified Segmentation via Randomized Smoothing Marc Fischer, Maximilian Baader, Martin Vechev

NeurIPS 2020 Certified Defense to Image Transformations via Randomized Smoothing Marc Fischer, Maximilian Baader, Martin Vechev

ICLR 2020 Universal Approximation with Certified Networks Maximilian Baader, Matthew Mirman, Martin Vechev

NeurIPS 2019 Certifying Geometric Robustness of Neural Networks Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin Vechev