Learning to Solve SMT Formulas. - Mislav Balunovic; Pavol Bielik; Martin T. Vechev (NeurIPS, 2018)

Learning to Fuzz from Symbolic Execution with Application to Smart Contracts. - Jingxuan He; Mislav Balunovic; Nodar Ambroladze; Petar Tsankov; Martin T. Vechev (CCS, 2019)

DL2: Training and Querying Neural Networks with Logic. - Marc Fischer 002; Mislav Balunovic; Dana Drachsler-Cohen; Timon Gehr; Ce Zhang 001; Martin T. Vechev (ICML, 2019)

Certifying Geometric Robustness of Neural Networks. - Mislav Balunovic; Maximilian Baader; Gagandeep Singh 001; Timon Gehr; Martin T. Vechev (NeurIPS, 2019)

Adversarial Training and Provable Defenses: Bridging the Gap. - Mislav Balunovic; Martin T. Vechev (ICLR, 2020)

Learning Certified Individually Fair Representations. - Anian Ruoss; Mislav Balunovic; Marc Fischer 002; Martin T. Vechev (NeurIPS, 2020)

Fast and Effective Robustness Certification for Recurrent Neural Networks. - Wonryong Ryou; Jiayu Chen; Mislav Balunovic; Gagandeep Singh 001; Andrei Marian Dan; Martin T. Vechev (CoRR, 2020)

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

Scalable Polyhedral Verification of Recurrent Neural Networks. - Wonryong Ryou; Jiayu Chen; Mislav Balunovic; Gagandeep Singh 001; Andrei Marian Dan; Martin T. Vechev (CAV (1), 2021)

Robustness Certification for Point Cloud Models. - Tobias Lorenz 002; Anian Ruoss; Mislav Balunovic; Gagandeep Singh 001; Martin T. Vechev (ICCV, 2021)

Certify or Predict: Boosting Certified Robustness with Compositional Architectures. - Mark Niklas Müller; Mislav Balunovic; Martin T. Vechev (ICLR, 2021)

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

Latent Space Smoothing for Individually Fair Representations. - Momchil Peychev; Anian Ruoss; Mislav Balunovic; Maximilian Baader; Martin T. Vechev (ECCV (13), 2022)

Bayesian Framework for Gradient Leakage. - Mislav Balunovic; Dimitar Iliev Dimitrov; Robin Staab; Martin T. Vechev (ICLR, 2022)

Fair Normalizing Flows. - Mislav Balunovic; Anian Ruoss; 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)

Data Leakage in Tabular Federated Learning. - Mark Vero; Mislav Balunovic; Dimitar I. Dimitrov; Martin T. Vechev (CoRR, 2022)

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

Data Leakage in Federated Averaging. - Dimitar Iliev Dimitrov; Mislav Balunovic; Nikola Konstantinov; Martin T. Vechev (Trans. Mach. Learn. Res., 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)

TabLeak: Tabular Data Leakage in Federated Learning. - Mark Vero; Mislav Balunovic; Dimitar Iliev Dimitrov; Martin T. Vechev (ICML, 2023)

Programmable Synthetic Tabular Data Generation. - Mark Vero; Mislav Balunovic; Martin T. Vechev (CoRR, 2023)

Beyond Memorization: Violating Privacy via Inference with Large Language Models. - Robin Staab; Mark Vero; Mislav Balunovic; Martin T. Vechev (ICLR, 2024)

CuTS: Customizable Tabular Synthetic Data Generation. - Mark Vero; Mislav Balunovic; Martin T. Vechev (ICML, 2024)

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. - Edoardo Debenedetti; Jie Zhang 107; Mislav Balunovic; Luca Beurer-Kellner; Marc Fischer 002; Florian Tramèr (NeurIPS, 2024)

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

Large Language Models are Advanced Anonymizers. - Robin Staab; Mark Vero; Mislav Balunovic; Martin T. Vechev (CoRR, 2024)

AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents. - Edoardo Debenedetti; Jie Zhang 107; Mislav Balunovic; Luca Beurer-Kellner; Marc Fischer 002; Florian Tramèr (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)

Formal and Statistical Certification of Robustness and Fairness for AI. - Mislav Balunovic (2024)

Language Models are Advanced Anonymizers. - Robin Staab; Mark Vero; Mislav Balunovic; 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)

ToolFuzz - Automated Agent Tool Testing. - Ivan Milev; Mislav Balunovic; Maximilian Baader; 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)

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

The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs. - Jasper Dekoninck; Ivo Petrov; Kristian Minchev; Mislav Balunovic; Martin T. Vechev; Miroslav Marinov; Maria Drencheva; Lyuba Konova; Milen Shumanov; Kaloyan Tsvetkov; Nikolay Drenchev; Lazar Todorov; et al. (CoRR, 2025)