4 papers
Empirical Comparison of Encoder-Based Language Models and Feature-Based Supervised Machine Learning Approaches to Automated Scoring of Long Essays
Kuo Wang, Haowei Hua, Pengfei Yan +2
Long context may impose challenges for encoder-only language models in text processing, specifically for automated scoring of essays. This study trained several commonly used encod…
Exploration of Summarization by Generative Language Models for Automated Scoring of Long Essays
Haowei Hua, Hong Jiao, Xinyi Wang
BERT and its variants are extensively explored for automated scoring. However, a limit of 512 tokens for these encoder-based models showed the deficiency in automated scoring of lo…
Exploring the Utilities of the Rationales from Large Language Models to Enhance Automated Essay Scoring
Hong Jiao, Hanna Choi, Haowei Hua
This study explored the utilities of rationales generated by GPT-4.1 and GPT-5 in automated scoring using Prompt 6 essays from the 2012 Kaggle ASAP data. Essay-based scoring was co…
Comparison of Scoring Rationales Between Large Language Models and Human Raters
Haowei Hua, Hong Jiao, Dan Song
Advances in automated scoring are closely aligned with advances in machine-learning and natural-language-processing techniques. With recent progress in large language models (LLMs)…