Towards Sparse Hierarchical Graph Classifiers. - Catalina Cangea; Petar Velickovic; Nikola Jovanovic 001; Thomas Kipf; Pietro Liò (CoRR, 2018)

Certified Defenses: Why Tighter Relaxations May Hurt Training? - Nikola Jovanovic 001; Mislav Balunovic; Maximilian Baader; Martin T. Vechev (CoRR, 2021)

Towards Robust Graph Contrastive Learning. - Nikola Jovanovic 001; Zhao Meng; Lukas Faber; Roger Wattenhofer (CoRR, 2021)

Private and Reliable Neural Network Inference. - Nikola Jovanovic 001; Marc Fischer 002; Samuel Steffen; Martin T. Vechev (CCS, 2022)

Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound. - Claudio Ferrari; Mark Niklas Müller; Nikola Jovanovic 001; Martin T. Vechev (ICLR, 2022)

LAMP: Extracting Text from Gradients with Language Model Priors. - Mislav Balunovic; Dimitar I. Dimitrov; Nikola Jovanovic 001; Martin T. Vechev (NeurIPS, 2022)

FARE: Provably Fair Representation Learning. - Nikola Jovanovic 001; Mislav Balunovic; Dimitar I. Dimitrov; Martin T. Vechev (CoRR, 2022)

On the Paradox of Certified Training. - Nikola Jovanovic 001; Mislav Balunovic; Maximilian Baader; Martin T. Vechev (Trans. Mach. Learn. Res., 2022)

FARE: Provably Fair Representation Learning with Practical Certificates. - Nikola Jovanovic 001; Mislav Balunovic; Dimitar Iliev Dimitrov; Martin T. Vechev (ICML, 2023)

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning. - Kostadin Garov; Dimitar Iliev Dimitrov; Nikola Jovanovic 001; Martin T. Vechev (ICLR, 2024)

Watermark Stealing in Large Language Models. - Nikola Jovanovic 001; Robin Staab; Martin T. Vechev (ICML, 2024)

From Principle to Practice: Vertical Data Minimization for Machine Learning. - Robin Staab; Nikola Jovanovic 001; Mislav Balunovic; Martin T. Vechev (SP, 2024)

Back to the Drawing Board for Fair Representation Learning. - Angéline Pouget; Nikola Jovanovic 001; Mark Vero; Robin Staab; Martin T. Vechev (CoRR, 2024)

Discovering Clues of Spoofed LM Watermarks. - Thibaud Gloaguen; Nikola Jovanovic 001; Robin Staab; Martin T. Vechev (CoRR, 2024)

COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act. - Philipp Guldimann; Alexander Spiridonov; Robin Staab; Nikola Jovanovic 001; Mark Vero; Velko Vechev; Anna Gueorguieva; Mislav Balunovic; Nikola Konstantinov; Pavol Bielik; Petar Tsankov; Martin T. Vechev (CoRR, 2024)

Ward: Provable RAG Dataset Inference via LLM Watermarks. - Nikola Jovanovic 001; Robin Staab; Maximilian Baader; Martin T. Vechev (ICLR, 2025)

Black-Box Detection of Language Model Watermarks. - Thibaud Gloaguen; Nikola Jovanovic 001; Robin Staab; Martin T. Vechev (ICLR, 2025)

MathConstruct: Challenging LLM Reasoning with Constructive Proofs. - Mislav Balunovic; Jasper Dekoninck; Nikola Jovanovic 001; Ivo Petrov; Martin T. Vechev (CoRR, 2025)

Towards Watermarking of Open-Source LLMs. - Thibaud Gloaguen; Nikola Jovanovic 001; Robin Staab; Martin T. Vechev (CoRR, 2025)

BaxBench: Can LLMs Generate Correct and Secure Backends? - Mark Vero; Niels Mündler; Victor Chibotaru; Veselin Raychev; Maximilian Baader; Nikola Jovanovic 001; Jingxuan He; Martin T. Vechev (CoRR, 2025)

Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad. - Ivo Petrov; Jasper Dekoninck; Lyuben Baltadzhiev; Maria Drencheva; Kristian Minchev; Mislav Balunovic; Nikola Jovanovic 001; Martin T. Vechev (CoRR, 2025)

Robust LLM Fingerprinting via Domain-Specific Watermarks. - Thibaud Gloaguen; Robin Staab; Nikola Jovanovic 001; Martin T. Vechev (CoRR, 2025)

MathArena: Evaluating LLMs on Uncontaminated Math Competitions. - Mislav Balunovic; Jasper Dekoninck; Ivo Petrov; Nikola Jovanovic 001; Martin T. Vechev (CoRR, 2025)

Watermarking Autoregressive Image Generation. - Nikola Jovanovic 001; Ismail Labiad; Tomás Soucek; Martin T. Vechev; Pierre Fernandez (CoRR, 2025)

SoK: Data Minimization in Machine Learning. - Robin Staab; Nikola Jovanovic 001; Kimberly Mai; Prakhar Ganesh; Martin T. Vechev; Ferdinando Fioretto; Matthew Jagielski (CoRR, 2025)