Larger batch sizes for LLM dialogue coding in healthcare simulations improve speed and reduce energy consumption while decreasing coding accuracy compared to human labels.
MIT Press, Cambridge, MA (2006)
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Semester-long tracking of 96 students showed LLM usage fell 42.7 points and verification dropped 19.4 points in team work, with 18.9% of consistent individual users stopping entirely in teams.
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Scalable LLM-based Coding of Dialogue in Healthcare Simulation: Balancing Coding Performance, Processing Time, and Environmental Impact
Larger batch sizes for LLM dialogue coding in healthcare simulations improve speed and reduce energy consumption while decreasing coding accuracy compared to human labels.