4 papers
CogEvol: Towards Efficient and Reliable Learning Environment Generation
Shangqing Tu, Daniel Zhang-Li, Yucheng Wang +20
We present CogEvol, a family of models trained specifically for Learning Environment Generation: turning a course brief into a finished learning artifact (structured-JSON slides or…
Addressing Situated Teaching Needs: A Multi-Agent Framework for Automated Slide Adaptation
Binglin Liu, Yucheng Wang, Zheyuan Zhang +5
The adaptation of teaching slides to instructors' situated teaching needs, including pedagogical styles and their students' context, is a critical yet time-consuming task for educa…
Handling Students Dropouts in an LLM-driven Interactive Online Course Using Language Models
Yuanchun Wang, Yiyang Fu, Jifan Yu +7
Interactive online learning environments, represented by Massive AI-empowered Courses (MAIC), leverage LLM-driven multi-agent systems to transform passive MOOCs into dynamic, text-…
LongWriter-V: Enabling Ultra-Long and High-Fidelity Generation in Vision-Language Models
Shangqing Tu, Yucheng Wang, Daniel Zhang-Li +8
Existing Large Vision-Language Models (LVLMs) can process inputs with context lengths up to 128k visual and text tokens, yet they struggle to generate coherent outputs beyond 1,000…