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Fabio Rovai

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Preprint Aug 2026

Consistency Is Not Coherence: Orientation Search for Certified Alignments Between 4D Defence Upper Ontologies

We align three upper ontologies that sit under UK and NATO defence data infrastructure: the Information Exchange Standard (IES), the Higher Quality Data Model (HQDM) that underpins the National Digital Twin, and Basic Formal Ontology (BFO). No public alignment between IES and HQDM existed. Promoting a hand-curated 17-c...

F. Rovai · 0 citations
#artificial intelligence Preprint Sep 2026

Who Verifies the Graph? Misspecification Attacks on Causal Action Verification for Language Agents

Causal action verifiers gate an agent's state-changing tool calls by checking whether each proposed intervention is identifiable against a committed action-state graph, and they issue a certificate that carries the identification argument and a one-sided lower confidence bound. One such verifier, CIVeX, reports zero fa...

F. Rovai · 0 citations
#artificial intelligence Preprint Sep 2026

Independent Verification Paths Are Not Independent: A Case Study of Common-Mode Failure in a Satellite Catalogue Pipeline

A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse to exit when they disagree, but one such gate failing is reported, in a cross-catalogue integrity study of two open registers of Earth-orbiting objects.

Fabio Rovai · 0 citations
Preprint Aug 2026

Proving the Utility of Large Language Models in Cybersecurity Simulations: A Comprehensive Examination

YAML is employed as a structured representation format for simulating complex network configurations, thereby enabling Large Language Model-driven pipelines to support and improve reinforcement learning (RL) agent training, and underscore the transformative potential of integrating LLMs into cybersecurity research.

S. Kampakis, F. Rovai, Marcos Charalambides et al. · 1 citation

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