33 citations · 37 across the 7 of their papers we have counts for
4 papers · 1 filter
Dense Contexts Are Hard Contexts: Lexical Density Limits Effective Context in LLMs
Giovanni Dettori, Matteo Boffa, Danilo Giordano +2
Input length and the position of relevant information are widely cited as the primary causes of degraded LLM long-context performance. Here, we study lexical density -- the rate at…
Autonomous LLM Agents & CTFs: A Second Look
Youness Bouchari, Matteo Boffa, Marco Mellia +3
Large Language Model (LLM) agents are increasingly proposed to automate offensive security tasks, with recent studies reporting near human-level success rates in Capture-the-Flag (…
Improving Generalization on Cybersecurity Tasks with Multi-Modal Contrastive Learning
Jianan Huang, Rodolfo V. Valentim, Luca Vassio +4
The use of ML in cybersecurity has long been impaired by generalization issues: Models that work well in controlled scenarios fail to maintain performance in production. The root c…
Towards Agentic Honeynet Configuration
Federico Mirra, Matteo Boffa, Idilio Drago +2
Honeypots are deception systems that emulate vulnerable services to collect threat intelligence. While deploying many honeypots increases the opportunity to observe attacker behavi…