3 papers
cs.HC2026
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…
cs.HC2026
Assistive Robots and Reasonable Work Assignment Reduce Perceived Stigma toward Persons with Disabilities
Stina Klein, Birgit Prodinger, Elisabeth André +2
Robots are becoming more prominent in assisting persons with disabilities (PwD). Whilst there is broad consensus that robots can assist in mitigating physical impairments, the exte…
cs.AI2026
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…