Maximilian Baader

46 papers A* 15Journal 29Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Unified Approach to Routing and Cascading for LLMs. ICML Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	Adaptive Generation of Bias-Eliciting Questions for LLMs. CoRR Robin Staab, Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	AutoBaxBuilder: Bootstrapping Code Security Benchmarking. CoRR Tobias von Arx, Niels Mündler, Mark Vero, Maximilian Baader, Martin T. Vechev
2025	A*	`conf`	BaxBench: Can LLMs Generate Correct and Secure Backends? ICML Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanovic, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	BaxBench: Can LLMs Generate Correct and Secure Backends? CoRR Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanovic, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	Certified Robustness to Data Poisoning in Gradient-Based Training. Trans. Mach. Learn. Res. Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
2025	J	`jnl`	CommandSans: Securing AI Agents with Surgical Precision Prompt Sanitization. CoRR Debeshee Das, Luca Beurer-Kellner, Marc Fischer, Maximilian Baader
2025	A*	`conf`	GRAIN: Exact Graph Reconstruction from Gradients. ICLR Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar Iliev Dimitrov, Martin T. Vechev
2025	J	`jnl`	GRAIN: Exact Graph Reconstruction from Gradients. CoRR Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar I. Dimitrov, Martin T. Vechev
2025	J	`jnl`	Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations. Trans. Mach. Learn. Res. Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin T. Vechev
2025	A*	`conf`	Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation. ICLR Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	SPEAR++: Scaling Gradient Inversion via Sparsely-Used Dictionary Learning. CoRR Alexander B. Bordetsky, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	ToolFuzz - Automated Agent Tool Testing. CoRR Ivan Milev, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2025	A*	`conf`	Ward: Provable RAG Dataset Inference via LLM Watermarks. ICLR Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev
2024	J	`jnl`	A Unified Approach to Routing and Cascading for LLMs. CoRR Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2024	J	`jnl`	Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
2024	A*	`conf`	DAGER: Exact Gradient Inversion for Large Language Models. NeurIPS Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	DAGER: Exact Gradient Inversion for Large Language Models. CoRR Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	Evading Data Contamination Detection for Language Models is (too) Easy. CoRR Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin T. Vechev
2024	—	`—`	Expressivity of Certified Neural Networks. Maximilian Baader
2024	A*	`conf`	Expressivity of ReLU-Networks under Convex Relaxations. ICLR Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
2024	J	`jnl`	Overcoming the Paradox of Certified Training with Gaussian Smoothing. CoRR Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin T. Vechev
2024	J	`jnl`	Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation. CoRR Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2024	A*	`conf`	SPEAR: Exact Gradient Inversion of Batches in Federated Learning. NeurIPS Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	SPEAR: Exact Gradient Inversion of Batches in Federated Learning. CoRR Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	Ward: Provable RAG Dataset Inference via LLM Watermarks. CoRR Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev
2023	J	`jnl`	Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. CoRR Benjamin Bichsel, Maximilian Baader, Anouk Paradis, Martin T. Vechev
2023	J	`jnl`	Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. Quantum Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin T. Vechev
2023	J	`jnl`	Expressivity of ReLU-Networks under Convex Relaxations. CoRR Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
2022	—	`conf`	Latent Space Smoothing for Individually Fair Representations. ECCV (13) Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2022	J	`jnl`	On the Paradox of Certified Training. Trans. Mach. Learn. Res. Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2022	J	`jnl`	The Fundamental Limits of Neural Networks for Interval Certified Robustness. Trans. Mach. Learn. Res. Matthew Mirman, Maximilian Baader, Martin T. Vechev
2021	J	`jnl`	Certified Defenses: Why Tighter Relaxations May Hurt Training? CoRR Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2021	A*	`conf`	Efficient Certification of Spatial Robustness. AAAI Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
2021	A*	`conf`	Fast and precise certification of transformers. PLDI Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev
2021	J	`jnl`	Latent Space Smoothing for Individually Fair Representations. CoRR Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2021	A*	`conf`	Scalable Certified Segmentation via Randomized Smoothing. ICML Marc Fischer, Maximilian Baader, Martin T. Vechev
2021	J	`jnl`	Scalable Certified Segmentation via Randomized Smoothing. CoRR Marc Fischer, Maximilian Baader, Martin T. Vechev
2021	J	`jnl`	The Fundamental Limits of Interval Arithmetic for Neural Networks. CoRR Matthew Mirman, Maximilian Baader, Martin T. Vechev
2020	J	`jnl`	Certification of Semantic Perturbations via Randomized Smoothing. CoRR Marc Fischer, Maximilian Baader, Martin T. Vechev
2020	A*	`conf`	Certified Defense to Image Transformations via Randomized Smoothing. NeurIPS Marc Fischer, Maximilian Baader, Martin T. Vechev
2020	J	`jnl`	Efficient Certification of Spatial Robustness. CoRR Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
2020	A*	`conf`	Silq: a high-level quantum language with safe uncomputation and intuitive semantics. PLDI Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin T. Vechev
2020	A*	`conf`	Universal Approximation with Certified Networks. ICLR Maximilian Baader, Matthew Mirman, Martin T. Vechev
2019	A*	`conf`	Certifying Geometric Robustness of Neural Networks. NeurIPS Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev
2019	J	`jnl`	Universal Approximation with Certified Networks. CoRR Maximilian Baader, Matthew Mirman, Martin T. Vechev