AI RESEARCH
Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction
arXiv CS.AI
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ArXi:2602.23312v2 Announce Type: replace-cross Leader-follower interaction is an important paradigm in human-robot interaction (HRI). Yet, assigning roles in real time remains challenging for resource-constrained mobile and assistive robots. While large language models (LLMs) have shown promise for natural communication, their size and latency limit on-device deployment. Small language models (SLMs) offer a potential alternative, but their effectiveness for role classification in HRI has not been systematically evaluated.