collaborators

5 papers

cs.CR2026

Firewalls to Secure Dynamic LLM Agentic Networks

Sahar Abdelnabi, Amr Gomaa, Eugene Bagdasarian +2

The emergence of agent-to-agent communication protocols mirrors the early internet: powerful connectivity with minimal security infrastructure. When AI agents communicate on behalf…

cs.LG2026

The Distillation Game: Adaptive Attacks & Efficient Defenses

Youssef Allouah, Mahdi Haghifam, Sanmi Koyejo +1

Distillation attacks create a deployment trade-off for model providers: the same outputs that make a model more useful can also make it easier to imitate. We study this trade-off t…

cs.AI2026

Generalization in LLM Problem Solving: The Case of the Shortest Path

Yao Tong, Jiayuan Ye, Anastasia Borovykh +1

Whether language models can systematically generalize remains actively debated. Yet empirical performance is jointly shaped by multiple factors such as training data, training para…

cs.AI2025

Contextual Integrity in LLMs via Reasoning and Reinforcement Learning

Guangchen Lan, Huseyin A. Inan, Sahar Abdelnabi +5

As the era of autonomous agents making decisions on behalf of users unfolds, ensuring contextual integrity (CI) -- what is the appropriate information to share while carrying out a…

cs.CL2025

The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text

Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin +2

How much information about training samples can be leaked through synthetic data generated by Large Language Models (LLMs)? Overlooking the subtleties of information flow in synthe…