AINeutralarXiv – CS AI · Feb 274/107
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Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction
Researchers benchmarked small language models (SLMs) for leader-follower role classification in human-robot interaction, finding that fine-tuned Qwen2.5-0.5B achieves 86.66% accuracy with 22.2ms latency. The study demonstrates SLMs can effectively handle real-time role assignment for resource-constrained robots, though performance degrades with increased dialogue complexity.