collaborators

5 papers

cs.CL2026

ToolFlood: Beyond Selection -- Hiding Valid Tools from LLM Agents via Semantic Covering

Hussein Jawad, Nicolas J-B Brunel

Large Language Model (LLM) agents increasingly use external tools for complex tasks and rely on embedding-based retrieval to select a small top-k subset for reasoning. As these sys…

cs.CR2026

PSM: Prompt Sensitivity Minimization via LLM-Guided Black-Box Optimization

Huseein Jawad, Nicolas Brunel

System prompts are critical for guiding the behavior of Large Language Models (LLMs), yet they often contain proprietary logic or sensitive information, making them a prime target…

stat.ME2025

Shape Analysis of Euclidean Curves under Frenet-Serret Framework

Perrine Chassat, Juhyun Park, Nicolas Brunel

Geometric frameworks for analyzing curves are common in applications as they focus on invariant features and provide visually satisfying solutions to standard problems such as comp…

cs.AI2025

Towards a rigorous evaluation of RAG systems: the challenge of due diligence

Grégoire Martinon, Alexandra Lorenzo de Brionne, Jérôme Bohard +3

The rise of generative AI, has driven significant advancements in high-risk sectors like healthcare and finance. The Retrieval-Augmented Generation (RAG) architecture, combining la…

cs.CL2025

Towards Universal and Black-Box Query-Response Only Attack on LLMs with QROA

Hussein Jawad, Yassine Chenik, Nicolas J. -B. Brunel

The rapid adoption of Large Language Models (LLMs) has exposed critical security and ethical vulnerabilities, particularly their susceptibility to adversarial manipulations. This p…