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This paper evaluates the use of small language models (SLMs) to assist title and abstract screening in systematic reviews of social-physical human-robot interaction (spHRI). While SLMs did not match human performance, they operated locally at high speed and identified additional relevant papers, demonstrating their potential to augment human reviewers for large-scale literature reviews.