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…
Leveraging Knowledge Graphs and LLMs for Structured Generation of Misinformation
Sania Nayab, Marco Simoni, Giulio Rossolini
The rapid spread of misinformation, further amplified by recent advances in generative AI, poses significant threats to society, impacting public opinion, democratic stability, and…