3 citations · 10 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
Scaling Human Activity Recognition: A Comparative Evaluation of Synthetic Data Generation and Augmentation Techniques
Zikang Leng, Archith Iyer, Thomas Plötz
Human activity recognition (HAR) is often limited by the scarcity of labeled datasets due to the high cost and complexity of real-world data collection. To mitigate this, recent wo…
AgentSense: Virtual Sensor Data Generation Using LLM Agents in Simulated Home Environments
Zikang Leng, Megha Thukral, Yaqi Liu +4
A major challenge in developing robust and generalizable Human Activity Recognition (HAR) systems for smart homes is the lack of large and diverse labeled datasets. Variations in h…
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…