Martin Gubri

According to our database, Martin Gubri authored at least 17 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers.

Tommaso Green, Martin Gubri, Haritz Puerto, Sangdoo Yun, Seong Joon Oh

CoRR, June, 2025

C-SEO Bench: Does Conversational SEO Work?

Haritz Puerto, Martin Gubri, Tommaso Green, Seong Joon Oh, Sangdoo Yun

CoRR, June, 2025

Testing Uniform Random Samplers: Methods, Datasets and Protocols.

Olivier Zeyen, Maxime Cordy, Martin Gubri, Gilles Perrouin, Mathieu Acher

CoRR, March, 2025

Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models.

Haritz Puerto, Martin Gubri, Sangdoo Yun, Seong Joon Oh

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

2024

Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models.

Adam Davies, Elisa Nguyen, Michael Simeone, Erik Johnston, Martin Gubri

CoRR, 2024

Calibrating Large Language Models Using Their Generations Only.

Dennis Ulmer, Martin Gubri, Hwaran Lee, Sangdoo Yun, Seong Joon Oh

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification.

Martin Gubri, Dennis Ulmer, Hwaran Lee, Sangdoo Yun, Seong Joon Oh

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

What Matters in Model Training to Transfer Adversarial Examples.

Martin Gubri

PhD thesis, 2023

Going Further: Flatness at the Rescue of Early Stopping for Adversarial Example Transferability.

Martin Gubri, Maxime Cordy, Yves Le Traon

CoRR, 2023

ProPILE: Probing Privacy Leakage in Large Language Models.

Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, Seong Joon Oh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Efficient and transferable adversarial examples from bayesian neural networks.

Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen

Proceedings of the Uncertainty in Artificial Intelligence, 2022

LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity.

Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen

Proceedings of the Computer Vision - ECCV 2022, 2022

Influence-driven data poisoning in graph-based semi-supervised classifiers.

Adriano Franci, Maxime Cordy, Martin Gubri, Mike Papadakis, Yves Le Traon

Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022

2020

Effective and Efficient Data Poisoning in Semi-Supervised Learning.

Adriano Franci, Maxime Cordy, Martin Gubri, Mike Papadakis, Yves Le Traon

CoRR, 2020

Efficient and Transferable Adversarial Examples from Bayesian Neural Networks.

Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon

CoRR, 2020

Search-based adversarial testing and improvement of constrained credit scoring systems.

Salah Ghamizi, Maxime Cordy, Martin Gubri, Mike Papadakis, Andrey Boytsov, Yves Le Traon, Anne Goujon

Proceedings of the ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020

2018

Adversarial Perturbation Intensity Achieving Chosen Intra-Technique Transferability Level for Logistic Regression.

Martin Gubri

CoRR, 2018