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cs.IR2025★ 1 cited
Can We Hide Machines in the Crowd? Quantifying Equivalence in LLM-in-the-loop Annotation Tasks
Jiaman He, Zikang Leng, Dana McKay +2
Many evaluations of large language models (LLMs) in text annotation focus primarily on the correctness of the output, typically comparing model-generated labels to human-annotated…
cs.IR2025★ 2 cited
Characterising Topic Familiarity and Query Specificity Using Eye-Tracking Data
Jiaman He, Zikang Leng, Dana McKay +2
Eye-tracking data has been shown to correlate with a user's knowledge level and query formulation behaviour. While previous work has focused primarily on eye gaze fixations for att…