From the 1 of 10 linked papers with an AI index.
10 papers
CyberLLM: A Multi-Agent LLM Framework for Autonomous Detection and Guarded Response in Automotive Cybersecurity
Nenad Petrovic, Oussama Jeddou, Feres Ben Fraj +4
Software-Defined Vehicles (SDVs) expand the automotive attack surface across source code, runtime logs, and deployment topologies, while safety constraints forbid autonomous agents…
Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis
Linus Sander, Fengjunjie Pan, Vahid Zolfaghari +3
The paper identifies four design principles for building scalable large‑language‑model‑driven multi‑agent systems, proposes a reference architecture based on a constrained directed…
GenAI-Driven Approach to RISC-V Supply Chain Exploration
Nenad Petrovic, Andre Schamschurko, Yingjie Xu +1
This paper presents an LLM-empowered workflow for RISC-V supply chain analysis, integrating Vision-Language Models (VLMs) and Model-Driven Engineering (MDE) to enable comprehensive…
CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs
Xingcheng Zhou, Hao Guo, Rui Song +5
Safety-critical traffic reasoning requires contrastive consistency: models must detect true hazards when an accident occurs, and reliably reject plausible-but-false hypotheses unde…
From Code to Road: A Vehicle-in-the-Loop and Digital Twin-Based Framework for Central Car Server Testing in Autonomous Driving
Chengdong Wu, Sven Kirchner, Nils Purschke +9
Simulation is one of the most essential parts in the development stage of automotive software. However, purely virtual simulations often struggle to accurately capture all real-wor…
LLM-Empowered Event-Chain Driven Code Generation for ADAS in SDV systems
Nenad Petrovic, Norbert Kroth, Axel Torschmied +9
This paper presents an event-chain-driven, LLM-empowered workflow for generating validated, automotive code from natural-language requirements. A Retrieval-Augmented Generation (RA…