5 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.CL2026
AI Cosmos: An Agentic Infra for Situated Learning
AI Cosmos Team, Jinfeng Zhou, Yuxuan Chen +32
Large language models (LLMs) can improve task performance during learning, yet these gains do not necessarily reflect learners' ability to thereafter apply the knowledge and skills…
cs.CY2025★ 1 cited
Which Type of Students can LLMs Act? Investigating Authentic Simulation with Graph-based Human-AI Collaborative System
Haoxuan Li, Jifan Yu, Xin Cong +6
While rapid advances in large language models (LLMs) are reshaping data-driven intelligent education, accurately simulating students remains an important but challenging bottleneck…
cs.CY2024★ 5 cited
From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Jifan Yu, Zheyuan Zhang, Daniel Zhang-li +30
Since the first instances of online education, where courses were uploaded to accessible and shared online platforms, this form of scaling the dissemination of human knowledge to r…