collaborators

8 papers

cs.CL2026

Metaphor Is Not All Attention Needs

Olga Sorokoletova, Francesco Giarrusso, Giacomo De Luca +6

Large language models are increasingly deployed in safety-critical applications, where their ability to resist harmful instructions is essential. Although post-training aims to mak…

cs.CY2026

Learning from Mistakes: Can LLM Self-Recover after Misalignment?

Olga E. Sorokoletova, Francesco Giarrusso, Vincenzo Suriani +1

Responsible AI initiatives place great emphasis on the safety of Large Language Model (LLM)-based systems. In particular, it has become standard practice to subject these models to…

cs.CL2026

Guarding the Guardrails: A Taxonomy-Driven Approach to Jailbreak Detection

Francesco Giarrusso, Olga E. Sorokoletova, Vincenzo Suriani +1

Jailbreaking techniques pose a significant threat to the safety of Large Language Models (LLMs). Existing defenses typically focus on single-turn attacks, lack coverage across lang…

cs.GT2026

Institutional AI: Governing LLM Collusion in Multi-Agent Cournot Markets via Public Governance Graphs

Marcantonio Bracale Syrnikov, Federico Pierucci, Marcello Galisai +6

Multi-agent LLM ensembles can converge on coordinated, socially harmful equilibria. This paper advances an experimental framework for evaluating Institutional AI, our system-level…

cs.CY2026

Institutional AI: A Governance Framework for Distributional AGI Safety

Federico Pierucci, Marcello Galisai, Marcantonio Syrnikov Bracale +6

As LLM-based systems increasingly operate as agents embedded within human social and technical systems, alignment can no longer be treated as a property of an isolated model, but m…

cs.CL2026

From Adversarial Poetry to Adversarial Tales: An Interpretability Research Agenda

Piercosma Bisconti, Marcello Galisai, Matteo Prandi +6

Safety mechanisms in LLMs remain vulnerable to attacks that reframe harmful requests through culturally coded structures. We introduce Adversarial Tales, a jailbreak technique that…