collaborators

7 papers

cs.CR2026

CyberForge: Verified Vulnerability Injection at Repository Level for Cybersecurity Agent Training

Amine Lbath, Manan Suri, Aurelien Delaitre +4

Despite recent advances, frontier large language model (LLM) agents remain limited in discovering and patching complex vulnerabilities in real-world software. Generally available a…

cs.LG2026

JEPAMatch: Geometric Representation Shaping for Semi-Supervised Learning

Ali Aghababaei-Harandi, Aude Sportisse, Massih-Reza Amini

Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learning models when labeled data a…

cs.CR2026

AVIATOR: Towards AI-Agentic Vulnerability Injection Workflow for High-Fidelity, Large-Scale Code Security Dataset

Amine Lbath, Massih-Reza Amini, Aurelien Delaitre +1

The increasing complexity of software systems and the sophistication of cyber-attacks have underscored the need for reliable automated software vulnerability detection. Data-driven…

cs.CV2025

Stylized Meta-Album: Group-bias injection with style transfer to study robustness against distribution shifts

Romain Mussard, Aurélien Gauffre, Ihsan Ullah +4

We introduce Stylized Meta-Album (SMA), a new image classification meta-dataset comprising 24 datasets (12 content datasets, and 12 stylized datasets), designed to advance studies…

cs.LG2025

Unified Framework for Pre-trained Neural Network Compression via Decomposition and Optimized Rank Selection

Ali Aghababaei-Harandi, Massih-Reza Amini

Despite their high accuracy, complex neural networks demand significant computational resources, posing challenges for deployment on resource constrained devices such as mobile pho…

cs.LG2025

Self-Training: A Survey

Massih-Reza Amini, Vasilii Feofanov, Loic Pauletto +3

Semi-supervised algorithms aim to learn prediction functions from a small set of labeled observations and a large set of unlabeled observations. Because this framework is relevant…