arXiv:2606.16206v2 Announce Type: replace
Abstract: Large language models are increasingly proposed as educational tutors, yet stronger task-solving ability does not necessarily imply stronger learni...
By Junyi Yao, Zihao Zheng, Baichuan Li
arXiv:2606. 06546v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know.
By Tao Liu, Ye Lu, Ruohua Zhang, Siyu Song, Wentao Liu, Aimin Zhou, Hao Hao
arXiv:2605.14322v4 Announce Type: replace
Abstract: Language agents are increasingly deployed in professional workflows, yet tutoring remains a high-stakes capability that existing evaluations only p...
By Zixin Chen, Peng Liu, Rui Sheng, Haobo Li, Jianhong Tu, Xiaodong Deng, Kashun Shum, Dayiheng Liu, Huamin Qu
arXiv:2609.28470v1 Announce Type: new
Abstract: Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advanc...
By Curtis Northcutt, Inaara Hasmani, Kevin Feng, Trevor Khangi, Andreas Plesner, Jonas Mueller
arXiv:2608. 03206v1 Announce Type: cross Abstract: Large language models (LLMs) power educational applications from tutoring to essay scoring, but each is a point solution to a single task, and only recently have these point solutions been integrated into agents operating over a learning management system (LMS).
By Unggi Lee, Sookbun Lee, Yeil Jeong, Eunjoo Lee, Minchul Shin, Hoilym Kwon
arXiv:2606. 12422v1 Announce Type: cross Abstract: The integration of large language models (LLMs) into educational assessment represents a transformative shift in classroom grading practices.
By Zewei Tian, Alex Liu, Lief Esbenshade, Michael Xiao, Zachary Zhang, Yulia L\'apicus, Thomas Han, Kevin He, Min Sun