Open-source large language models (LLMs) research has made significant progress, but most studies predominantly focus on general-purpose English data, which poses challenges for LLM research in Chinese education. To address this, this research first reviewed and synthesized the core technologies of representative open-source LLMs, and designed an advanced 1.5B-parameter LLM tailored for the Chinese education field. Chinese education large language model (CELLM) is trained from scratch, involving two stages, namely, pre-training and instruction fine-tuning. In the pre-training phase, an open-source dataset is utilized for the Chinese education domain. During the instruction fine-tuning stage, the Chinese instruction dataset is developed and open-sourced, comprising over 258,000 data entries. Finally, the results and analysis of CELLM across multiple evaluation datasets are presented, which provides a reference baseline performance for future research. All of the models, data, and codes are open-source to foster community research on LLMs in the Chinese education domain. 

The Quantum Education Summit event, hosted at CosmoCaixa Science Museum of Barcelona, will gather more than 300 participants from five different continents.

The topics of the conference will cover the full spectrum of quantum education:  from foundational curriculum design, workforce training and inclusive global participation to policy strategies, educational innovations, and outreach efforts that advance accessibility and broaden the impact of quantum learning worldwide.

Keynote speakers include Nobel Laureate Carl Wieman, from Stanford University, Maité Depuis, from Perimeter Institute of Canada, and Eboney Hearn, from MIT Introduction to Technology, Engineering and Science.