Robin Staab - RankMe

38 papers A* 12Journal 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified Framework for LLM Watermarks. CoRR Thibaud Gloaguen, Robin Staab, Nikola Jovanovic, Martin T. Vechev
2025	J	`jnl`	Adaptive Generation of Bias-Eliciting Questions for LLMs. CoRR Robin Staab, Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	A*	`conf`	Black-Box Detection of Language Model Watermarks. ICLR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2025	A*	`conf`	Discovering Spoofing Attempts on Language Model Watermarks. ICML Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2025	J	`jnl`	Fewer Weights, More Problems: A Practical Attack on LLM Pruning. CoRR Kazuki Egashira, Robin Staab, Thibaud Gloaguen, Mark Vero, Martin T. Vechev
2025	J	`jnl`	Finetuning-Activated Backdoors in LLMs. CoRR Thibaud Gloaguen, Mark Vero, Robin Staab, Martin T. Vechev
2025	A*	`conf`	Language Models are Advanced Anonymizers. ICLR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2025	A*	`conf`	Mind the Gap: A Practical Attack on GGUF Quantization. ICML Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	Mind the Gap: A Practical Attack on GGUF Quantization. CoRR Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	MixAT: Combining Continuous and Discrete Adversarial Training for LLMs. CoRR Csaba Dékány, Stefan Balauca, Robin Staab, Dimitar I. Dimitrov, Martin T. Vechev
2025	J	`jnl`	Pay Attention to the Triggers: Constructing Backdoors That Survive Distillation. CoRR Giovanni De Muri, Mark Vero, Robin Staab, Martin T. Vechev
2025	J	`jnl`	Robust LLM Fingerprinting via Domain-Specific Watermarks. CoRR Thibaud Gloaguen, Robin Staab, Nikola Jovanovic, Martin T. Vechev
2025	J	`jnl`	SoK: Data Minimization in Machine Learning. CoRR Robin Staab, Nikola Jovanovic, Kimberly Mai, Prakhar Ganesh, Martin T. Vechev, Ferdinando Fioretto, Matthew Jagielski
2025	J	`jnl`	Towards Watermarking of Open-Source LLMs. CoRR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2025	A*	`conf`	Ward: Provable RAG Dataset Inference via LLM Watermarks. ICLR Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	Watermarking Diffusion Language Models. CoRR Thibaud Gloaguen, Robin Staab, Nikola Jovanovic, Martin T. Vechev
2024	A*	`conf`	A Synthetic Dataset for Personal Attribute Inference. NeurIPS Hanna Yukhymenko, Robin Staab, Mark Vero, Martin T. Vechev
2024	J	`jnl`	A Synthetic Dataset for Personal Attribute Inference. CoRR Hanna Yukhymenko, Robin Staab, Mark Vero, Martin T. Vechev
2024	J	`jnl`	Back to the Drawing Board for Fair Representation Learning. CoRR Angéline Pouget, Nikola Jovanovic, Mark Vero, Robin Staab, Martin T. Vechev
2024	A*	`conf`	Beyond Memorization: Violating Privacy via Inference with Large Language Models. ICLR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2024	J	`jnl`	Black-Box Detection of Language Model Watermarks. CoRR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2024	J	`jnl`	COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act. CoRR Philipp Guldimann, Alexander Spiridonov, Robin Staab, Nikola Jovanovic, Mark Vero, Velko Vechev, Anna Gueorguieva, Mislav Balunovic, Nikola Konstantinov, Pavol Bielik, Petar Tsankov, Martin T. Vechev
2024	J	`jnl`	Discovering Clues of Spoofed LM Watermarks. CoRR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2024	A*	`conf`	Exploiting LLM Quantization. NeurIPS Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin T. Vechev
2024	J	`jnl`	Exploiting LLM Quantization. CoRR Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin T. Vechev
2024	A*	`conf`	From Principle to Practice: Vertical Data Minimization for Machine Learning. SP Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev
2024	J	`jnl`	Large Language Models are Advanced Anonymizers. CoRR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2024	A*	`conf`	Private Attribute Inference from Images with Vision-Language Models. NeurIPS Batuhan Tömekçe, Mark Vero, Robin Staab, Martin T. Vechev
2024	J	`jnl`	Private Attribute Inference from Images with Vision-Language Models. CoRR Batuhan Tömekçe, Mark Vero, Robin Staab, Martin T. Vechev
2024	J	`jnl`	Ward: Provable RAG Dataset Inference via LLM Watermarks. CoRR Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev
2024	A*	`conf`	Watermark Stealing in Large Language Models. ICML Nikola Jovanovic, Robin Staab, Martin T. Vechev
2024	J	`jnl`	Watermark Stealing in Large Language Models. CoRR Nikola Jovanovic, Robin Staab, Martin T. Vechev
2023	J	`jnl`	Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks. Proc. ACM Program. Lang. Mark Niklas Müller, Marc Fischer, Robin Staab, Martin T. Vechev
2023	J	`jnl`	Beyond Memorization: Violating Privacy Via Inference with Large Language Models. CoRR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2023	J	`jnl`	From Principle to Practice: Vertical Data Minimization for Machine Learning. CoRR Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev
2022	A*	`conf`	Bayesian Framework for Gradient Leakage. ICLR Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab, Martin T. Vechev
2021	J	`jnl`	Bayesian Framework for Gradient Leakage. CoRR Mislav Balunovic, Dimitar I. Dimitrov, Robin Staab, Martin T. Vechev
2021	J	`jnl`	Effective Certification of Monotone Deep Equilibrium Models. CoRR Mark Niklas Müller, Robin Staab, Marc Fischer, Martin T. Vechev