Scalable Inference of Symbolic Adversarial Examples. - Dimitar I. Dimitrov; Gagandeep Singh 001; Timon Gehr; Martin T. Vechev (CoRR, 2020)

Fast and precise certification of transformers. - Gregory Bonaert; Dimitar I. Dimitrov; Maximilian Baader; Martin T. Vechev (PLDI, 2021)

Shared Certificates for Neural Network Verification. - Marc Fischer 002; Christian Sprecher; Dimitar I. Dimitrov; Gagandeep Singh 001; Martin T. Vechev (CAV (1), 2022)

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

Provably Robust Adversarial Examples. - Dimitar Iliev Dimitrov; Gagandeep Singh 001; Timon Gehr; 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)

Group and Attack: Auditing Differential Privacy. - Johan Lokna; Anouk Paradis; Dimitar I. Dimitrov; Martin T. Vechev (CCS, 2023)

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)

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

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

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

BgGPT 1.0: Extending English-centric LLMs to other languages. - Anton Alexandrov; Veselin Raychev; Dimitar I. Dimitrov; Ce Zhang 001; Martin T. Vechev; Kristina Toutanova (CoRR, 2024)

GRAIN: Exact Graph Reconstruction from Gradients. - Maria Drencheva; Ivo Petrov; Maximilian Baader; Dimitar Iliev Dimitrov; Martin T. Vechev (ICLR, 2025)

MixAT: Combining Continuous and Discrete Adversarial Training for LLMs. - Csaba Dékány; Stefan Balauca; Robin Staab; Dimitar I. Dimitrov; Martin T. Vechev (CoRR, 2025)

LARP: Learner-Agnostic Robust Data Prefiltering. - Kristian Minchev; Dimitar Iliev Dimitrov; Nikola Konstantinov (CoRR, 2025)