Max Lu

Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here

2025

pdf bib
How Model Size, Temperature, and Prompt Style Affect LLM-Human Assessment Score Alignment
Julie Jung | Max Lu | Sina Chole Benker | Dogus Darici
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers

We examined how model size, temperature, and prompt style affect Large Language Models’ (LLMs) alignment with human raters in assessing clinical reasoning skills. Model size emerged as a key factor in LLM-human score alignment. Findings reveal both the potential for scalable LLM-raters and the risks of relying on them exclusively.
Search
Co-authors
Venues
Fix data