collaborators

5 papers

cs.LG2025

Multi-LLM Collaboration for Medication Recommendation

Huascar Sanchez, Briland Hitaj, Jules Bergmann +1

As healthcare increasingly turns to AI for scalable and trustworthy clinical decision support, ensuring reliability in model reasoning remains a critical challenge. Individual larg…

cs.LG2025

LLM Chemistry Estimation for Multi-LLM Recommendation

Huascar Sanchez, Briland Hitaj

Multi-LLM collaboration promises accurate, robust, and context-aware solutions, yet existing approaches rely on implicit selection and output assessment without analyzing whether c…

cs.CR2025

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems

Vitor Hugo Galhardo Moia, Igor Jochem Sanz, Gabriel Antonio Fontes Rebello +3

The success and wide adoption of generative AI (GenAI), particularly large language models (LLMs), has attracted the attention of cybercriminals seeking to abuse models, steal sens…

cs.CR2025

Do You Trust Your Model? Emerging Malware Threats in the Deep Learning Ecosystem

Dorjan Hitaj, Giulio Pagnotta, Fabio De Gaspari +4

Training high-quality deep learning models is a challenging task due to computational and technical requirements. A growing number of individuals, institutions, and companies incre…

cs.CR2025

A Case Study on the Use of Representativeness Bias as a Defense Against Adversarial Cyber Threats

Briland Hitaj, Grit Denker, Laura Tinnel +9

Cyberspace is an ever-evolving battleground involving adversaries seeking to circumvent existing safeguards and defenders aiming to stay one step ahead by predicting and mitigating…