16 citations · 24 across the 19 of their papers we have counts for
8 papers · 1 filter
Words to World: Benchmarking LLMs in Interactive Physical Environments
Xinnan Dai, Kaiqi Yang, Yaxin Li +9
Words are increasingly becoming an interface for action: large language models (LLMs) can now invoke tools, operate devices, and make decisions that affect the physical world. Howe…
Think-Before-Speak: From Internal Evaluation to Public Expression in Multi-Agent Social Simulation
Kaiqi Yang, Tai-Quan Peng, Sanguk Lee +1
LLM-based multi-agent simulation offers a promising way to study social interaction, deliberation, and collective opinion dynamics. However, many existing dialogue simulation frame…
Optimizing In-Context Demonstrations for LLM-based Automated Grading
Yucheng Chu, Hang Li, Kaiqi Yang +4
Automated assessment of open-ended student responses is a critical capability for scaling personalized feedback in education. While large language models (LLMs) have shown promise…
Confusion-Aware Rubric Optimization for LLM-based Automated Grading
Yucheng Chu, Hang Li, Kaiqi Yang +4
Accurate and unambiguous guidelines are critical for large language model (LLM) based graders, yet manually crafting these prompts is often sub-optimal as LLMs can misinterpret exp…
How Uncertain Is the Grade? A Benchmark of Uncertainty Metrics for LLM-Based Automatic Assessment
Hang Li, Kaiqi Yang, Xianxuan Long +9
The rapid rise of large language models (LLMs) is reshaping the landscape of automatic assessment in education. While these systems demonstrate substantial advantages in adaptabili…
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…