1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…