5 papers
Safeguards for Speech2Speech LLM-Assistants: A Case Study in Automotive Applications
Gregor Endler, Sebastian Kraus, Lukas Stappen
Recent advances have introduced speech-to-speech (S2S) conversational assistants capable of producing natural-sounding interactions, including non-verbal cues like tonality and moo…
What Are You Doing? Effects of Intermediate Feedback from Agentic LLM In-Car Assistants During Multi-Step Processing
Johannes Kirmayr, Raphael Wennmacher, Khanh Huynh +3
Agentic AI assistants that autonomously perform multi-step tasks raise open questions for user experience: how should such systems communicate progress and reasoning during extende…
Agent2Agent Threats in Safety-Critical LLM Assistants: A Human-Centric Taxonomy
Lukas Stappen, Ahmet Erkan Turan, Johann Hagerer +1
The integration of Large Language Model (LLM)-based conversational agents into vehicles creates novel security challenges at the intersection of agentic AI, automotive safety, and…
CAR-bench: Evaluating the Consistency and Limit-Awareness of LLM Agents under Real-World Uncertainty
Johannes Kirmayr, Lukas Stappen, Elisabeth André
Existing benchmarks for Large Language Model (LLM) agents focus on task completion under idealistic settings but overlook reliability in real-world, user-facing applications. In do…
CarMem: Enhancing Long-Term Memory in LLM Voice Assistants through Category-Bounding
Johannes Kirmayr, Lukas Stappen, Phillip Schneider +2
In today's assistant landscape, personalisation enhances interactions, fosters long-term relationships, and deepens engagement. However, many systems struggle with retaining user p…