3 papers
cs.CV2026
Adversarial Camouflage
PaweÅ Borsukiewicz, Daniele Lunghi, Melissa Tessa +2
While the rapid development of facial recognition algorithms has enabled numerous beneficial applications, their widespread deployment has raised significant concerns about the ris…
cs.CR2026
How Secure is Secure Code Generation? Adversarial Prompts Put LLM Defenses to the Test
Melissa Tessa, Iyiola E. Olatunji, Aicha War +2
Recent secure code generation methods, using vulnerability-aware fine-tuning, prefix-tuning, and prompt optimization, claim to prevent LLMs from producing insecure code. However, t…
cs.IR2025
A Lay User Explainable Food Recommendation System Based on Hybrid Feature Importance Extraction and Large Language Models
Melissa Tessa, Diderot D. Cidjeu, Rachele Carli +4
Large Language Models (LLM) have experienced strong development in recent years, with varied applications. This paper uses LLMs to develop a post-hoc process that provides more ela…