MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series
Research paper by Ge Zhang and collaborators. Published 2024-05-29. Topics: Large Language Models, LLMs, GPT, Gemini, Claude.
Resource information
- Authors
- Ge Zhang, Scott Qu, Jiaheng Liu, Chenchen Zhang, Chenghua Lin, Chou Leuang Yu, Danny Pan, Esther Cheng, Jie Liu, Qunshu Lin, Raven Yuan, Tuney Zheng, Wei Pang, Xinrun Du, Yiming Liang, Yinghao Ma, Yizhi Li, Ziyang Ma, Bill Lin, Emmanouil Benetos, Huan Yang, Junting Zhou, Kaijing Ma, Minghao Liu, Morry Niu, Noah Wang, Quehry Que, Ruibo Liu, Sine Liu, Shawn Guo, Soren Gao, Wangchunshu Zhou, Xinyue Zhang, Yizhi Zhou, Yubo Wang, Yuelin Bai, Yuhan Zhang, Yuxiang Zhang, Zenith Wang, Zhenzhu Yang, Zijian Zhao, Jiajun Zhang, Wanli Ouyang, Wenhao Huang, Wenhu Chen
- Research topics
- Large Language Models, LLMs, GPT, Gemini, Claude, LLaMA-3, Pythia, Amber, OLMo, MAP-Neo, bilingual language model, pre-training corpus
- Publication date
- 2024-05-29
- Publication
- arXiv
- Last record update
- Nov 3, 2026
