Nikola Jovanovic

Affiliations:

ETH Zurich, Switzerland
Union University, Belgrade, Serbia (former)

According to our database¹, Nikola Jovanovic authored at least 24 papers between 2018 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2025

Watermarking Autoregressive Image Generation.

[BibT_eX]

[DOI]

CoRR, June, 2025

MathArena: Evaluating LLMs on Uncontaminated Math Competitions.

[BibT_eX]

[DOI]

CoRR, May, 2025

Robust LLM Fingerprinting via Domain-Specific Watermarks.

[BibT_eX]

[DOI]

CoRR, May, 2025

Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad.

[BibT_eX]

[DOI]

CoRR, March, 2025

BaxBench: Can LLMs Generate Correct and Secure Backends?

[BibT_eX]

[DOI]

CoRR, February, 2025

Towards Watermarking of Open-Source LLMs.

[BibT_eX]

[DOI]

CoRR, February, 2025

MathConstruct: Challenging LLM Reasoning with Constructive Proofs.

[BibT_eX]

[DOI]

CoRR, February, 2025

Black-Box Detection of Language Model Watermarks.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Ward: Provable RAG Dataset Inference via LLM Watermarks.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act.

[BibT_eX]

[DOI]

CoRR, 2024

Discovering Clues of Spoofed LM Watermarks.

[BibT_eX]

[DOI]

CoRR, 2024

Back to the Drawing Board for Fair Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2024

From Principle to Practice: Vertical Data Minimization for Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Security and Privacy, 2024

Watermark Stealing in Large Language Models.

[BibT_eX]

[DOI]

Nikola Jovanovic

Robin Staab

Martin T. Vechev

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning.

[BibT_eX]

[DOI]

Kostadin Garov

Dimitar Iliev Dimitrov

Nikola Jovanovic

Martin T. Vechev

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

FARE: Provably Fair Representation Learning with Practical Certificates.

[BibT_eX]

[DOI]

Nikola Jovanovic

Mislav Balunovic

Dimitar Iliev Dimitrov

Martin T. Vechev

Proceedings of the International Conference on Machine Learning, 2023

2022

On the Paradox of Certified Training.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

FARE: Provably Fair Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2022

LAMP: Extracting Text from Gradients with Language Model Priors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Private and Reliable Neural Network Inference.

[BibT_eX]

[DOI]

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021

Towards Robust Graph Contrastive Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Certified Defenses: Why Tighter Relaxations May Hurt Training?

[BibT_eX]

[DOI]

CoRR, 2021

2018

Towards Sparse Hierarchical Graph Classifiers.

[BibT_eX]

[DOI]

CoRR, 2018

Nikola Jovanovic

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