6 papers
On the Hidden Objective Biases of Group-based Reinforcement Learning
Aleksandar Fontana, Marco Simoni, Giulio Rossolini +2
Group-based reinforcement learning methods, like Group Relative Policy Optimization (GRPO), are widely used nowadays to post-train large language models. Despite their empirical su…
GTPO: Stabilizing Group Relative Policy Optimization via Gradient and Entropy Control
Marco Simoni, Aleksandar Fontana, Giulio Rossolini +2
Group Relative Policy Optimization (GRPO) is a promising policy-based approach for Large Language Model alignment, yet its performance is often limited by training instability and…
KGQuest: Template-Driven QA Generation from Knowledge Graphs with LLM-Based Refinement
Sania Nayab, Marco Simoni, Giulio Rossolini +1
The generation of questions and answers (QA) from knowledge graphs (KG) plays a crucial role in the development and testing of educational platforms, dissemination tools, and large…
TITAN: Graph-Executable Reasoning for Cyber Threat Intelligence
Marco Simoni, Aleksandar Fontana, Andrea Saracino +1
TITAN (Threat Intelligence Through Automated Navigation) is a framework that connects natural-language cyber threat queries with executable reasoning over a structured knowledge gr…
Improving LLM Reasoning for Vulnerability Detection via Group Relative Policy Optimization
Marco Simoni, Aleksandar Fontana, Giulio Rossolini +1
Improving and understanding the training dynamics and reasoning of Large Language Models (LLMs) has become essential for their deployment in AI-based security tools, such as softwa…
MoRSE: Bridging the Gap in Cybersecurity Expertise with Retrieval Augmented Generation
Marco Simoni, Andrea Saracino, Vinod P. +1
In this paper, we introduce MoRSE (Mixture of RAGs Security Experts), the first specialised AI chatbot for cybersecurity. MoRSE aims to provide comprehensive and complete knowledge…