AI RESEARCH
Seeking Information with RAG-Assistants: Does Model Size Matter in Human-AI Collaborations?
arXiv CS.AI
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ArXi:2605.00964v1 Announce Type: cross Much research on LLMs has focused on increasing benchmark performance. However, the evaluation of such models in real-world collaborative human-AI workflows has stayed behind. This work evaluates a chatbot-style assistant based on Retrieval-Augmented Generation (RAG) in a realistic multi-turn information-seeking scenario inspired by workplace settings where compliance with local legislation and secure handling of sensitive data are often key.