activity
20242026
most citedConcise Thoughts: Impact of Output Length on LLM Reasoning and Cost

4 citations · 4 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2026

DANTINOX: A Unified Framework for Multi-Paradigm Language Modeling

Marco Simoni, Aleksandar Fontana, Giulio Rossolini +1

Language generation research increasingly spans three paradigms: autoregressive decoding, discrete masked diffusion, and continuous flow-matching. Comparing them is difficult becau…

cs.LG2026

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…

cs.CL2025

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…

cs.AI2025

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…

cs.LG2025

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…

cs.CR2025

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…

cs.CR2024

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…

cs.CL2024★ 4 cited

Concise Thoughts: Impact of Output Length on LLM Reasoning and Cost

Sania Nayab, Giulio Rossolini, Marco Simoni +4

Today's large language models (LLMs) can solve challenging question-answering tasks, and prompt engineering techniques, such as chain-of-thought (CoT), have gained attention for en…