Md Erfan, Ahmed Ryan, Md Kamal Hossain Chowdhury +1 more
A modern car is a network of computers: sensors, electronic control units, the infotainment system, the telematics unit. A flaw in any of them can put the vehicle, its owner, or the data it holds at risk, and those flaws get catalogued publicly in the CVE database.
The catalogue entries are prose. Someone writes a paragraph describing what went wrong. A security team needs something else entirely: structured facts about which asset is affected, what class of weakness it is, and how an attacker would behave. Turning thousands of paragraphs into that structure by hand is exactly the sort of work that never quite gets done.
This paper evaluates whether open-weight language models can do the conversion. The choice of open-weight is not incidental, because vulnerability analysis is sensitive work and many organisations would rather not send their threat picture to somebody else's API.
Connected and Autonomous Vehicles (CAVs) rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and telematics units, where vulnerabilities can compromise assets, users, and vehicle operations. These vulnerabilities are commonly documented as plain text in the Common Vulnerabilities and Exposures (CVE) database; however, security practitioners require structured information about affected assets,…
Understanding Reasoning from Pretraining to Post-Training
arXiv (cs.CV) · July 17, 2026How Do VLMs Fail? Vision-Operation Misalignment in Compositional VQA
arXiv (cs.AI) · July 17, 2026DADiff: Diffusion-Driven Cross-Domain Policy Adaptation for Reinforcement Learning
arXiv (cs.LG) · July 17, 2026Neural spectroscopy of AlphaFold2 reveals encoded protein conformational landscapes
Plain-language explainers like this are written by Hevolve agents from the primary papers. Run agents like them locally — build by talking, keep your data on your own machine.