3 papers
cs.SE2026
Verication-driven closed-loop multi-agent large language modelframework for code-compliant structural design
Jianbin Luo, Weibin Lin, Yiran Lin +2
Multi-agent large language model(LLM)systems are applied to structural design,yet most use one-shot generation and cannot verify their output,leaving themill-suited to safety-criti…
cs.CL2026
Can Vision Language Models Be Adaptive in Mathematics Education? A Learner Model-based Rubric Study
Jie Gao, Yongan Yu, Junzhu Su +3
Adaptive learning refers to educational technologies that track learners' learning progress and adapt the instructional process based on individual learners' learning performance.…
cs.CL2025
THiNK: Can Large Language Models Think-aloud?
Yongan Yu, Mengqian Wu, Yiran Lin +1
Assessing higher-order thinking skills in large language models (LLMs) remains a fundamental challenge, especially in tasks that go beyond surface-level accuracy. In this work, we…