1 citations · 2 across the 14 of their papers we have counts for
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CrochetBench: Can Vision-Language Models Move from Describing to Doing in Crochet Domain?
Peiyu Li, Xiaobao Huang, Ting Hua +1
While multimodal large language models can describe visual content, their ability to generate executable procedures remains underexplored. CrochetBench presented in this paper eval…
Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks
Peiyu Li, Xiuxiu Tang, Si Chen +4
Evaluating large language models (LLMs) typically requires thousands of benchmark items, making the process expensive, slow, and increasingly impractical at scale. Existing evaluat…
Exploring Conversational Design Choices in LLMs for Pedagogical Purposes: Socratic and Narrative Approaches for Improving Instructor's Teaching Practice
Si Chen, Isabel R. Molnar, Peiyu Li +5
Large language models (LLMs) typically generate direct answers, yet they are increasingly used as learning tools. Studying instructors' usage is critical, given their role in teach…
LLMs4All: A Review of Large Language Models Across Academic Disciplines
Yanfang Ye, Zheyuan Zhang, Tianyi Ma +26
Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown t…
"Not in My Backyard": LLMs Uncover Online and Offline Social Biases Against Homelessness
Jonathan A. Karr, Benjamin F. Herbst, Matthew L. Sisk +5
Homelessness is a persistent social challenge, impacting millions worldwide. Over 876,000 people experiencing homelessness (PEH) were recorded in the U.S. in 2025. Social bias is a…
Building Scaffolding Dialogue Data with LLM-Simulated Novices
Si Chen, Izzy Molnar, Ting Hua +6
High-quality, multi-turn instructional dialogues between novices and experts are essential for developing AI systems that support teaching, learning, and decision-making. These dia…
FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE
Khiem Le, Tuan Tran, Ting Hua +1
Existing resource-adaptive LoRA federated fine-tuning methods enable clients to fine-tune models using compressed versions of global LoRA matrices, in order to accommodate various…