16 citations · 24 across the 19 of their papers we have counts for
6 papers · 1 filter
Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions
Hang Li, Tianlong Xu, Kaiqi Yang +5
The rise of large language models (LLMs) offers new opportunities for automatic error detection in education, particularly for math word problems (MWPs). While prior studies demons…
Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models
Tai-Quan Peng, Kaiqi Yang, Sanguk Lee +4
As large language models (LLMs) become increasingly embedded in civic, educational, and political information environments, concerns about their potential political bias have grown…
Exploring Social Desirability Response Bias in Large Language Models: Evidence from GPT-4 Simulations
Sanguk Lee, Kai-Qi Yang, Tai-Quan Peng +2
Large language models (LLMs) are employed to simulate human-like responses in social surveys, yet it remains unclear if they develop biases like social desirability response (SDR)…
A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization
Yucheng Chu, Hang Li, Kaiqi Yang +4
Open-ended short-answer questions (SAGs) have been widely recognized as a powerful tool for providing deeper insights into learners' responses in the context of learning analytics…
Content Knowledge Identification with Multi-Agent Large Language Models (LLMs)
Kaiqi Yang, Yucheng Chu, Taylor Darwin +6
Teachers' mathematical content knowledge (CK) is of vital importance and need in teacher professional development (PD) programs. Computer-aided asynchronous PD systems are the most…
Are Large Language Models (LLMs) Good Social Predictors?
Kaiqi Yang, Hang Li, Hongzhi Wen +3
The prediction has served as a crucial scientific method in modern social studies. With the recent advancement of Large Language Models (LLMs), efforts have been made to leverage L…