arXiv 2609.23088 · cs.CL · 2026-09-19
OmniEdu: Open Foundation Models for Learning and Teaching
Hao Liang, Qihan Lin, Meiyi Qiang, Linzhuang Sun, Hengyi Feng, Mingrui Chen, Sizhe Qiu, Wentao Zhang
Peking University
In latest · #21 2026-W39 #1 Added on 2026-10-21
One-line takeaway
OmniEdu is an open family of K-12 education foundation models covering problem solving, curriculum grounding, diagnosis and tutoring.
OmniEdu 是面向中小学教与学的开源基础模型家族，覆盖解题、课程对齐、学情诊断和教学引导。
Read on arXiv PDF Hugging Face discussion Code Project page
Topics & disciplines
More on LLMs
- Jeva: System One Models from First Principles ▲371
- Post-Training Leaves Behavioral Shadows on Unrelated Decisions ▲273
- PAR: Progress-Aligned Recurrence for Length Generalization in State Tracking ▲148
- MemT-1.0: Towards Memory-Native Evolution ▲119
- MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement ▲92
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.