3 papers
cs.CL2025
Automated Refinement of Essay Scoring Rubrics for Language Models via Reflect-and-Revise
Keno Harada, Lui Yoshida, Takeshi Kojima +2
The performance of Large Language Models (LLMs) is highly sensitive to the prompts they are given. Drawing inspiration from the field of prompt optimization, this study investigate…
cs.CL2025
Do We Need a Detailed Rubric for Automated Essay Scoring using Large Language Models?
Lui Yoshida
This study investigates the necessity and impact of a detailed rubric in automated essay scoring (AES) using large language models (LLMs). While using rubrics are standard in LLM-b…
cs.CL2024
The Impact of Example Selection in Few-Shot Prompting on Automated Essay Scoring Using GPT Models
Lui Yoshida
This study investigates the impact of example selection on the performance of au-tomated essay scoring (AES) using few-shot prompting with GPT models. We evaluate the effects of th…