April 15, 2024, 4:42 a.m. | Zhengde Zhang, Yiyu Zhang, Haodong Yao, Jianwen Luo, Rui Zhao, Bo Huang, Jiameng Zhao, Yipu Liao, Ke Li, Lina Zhao, Jun Cao, Fazhi Qi, Changzheng Yuan

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.08001v1 Announce Type: cross
Abstract: Large Language Models (LLMs) are undergoing a period of rapid updates and changes, with state-of-the-art (SOTA) model frequently being replaced. When applying LLMs to a specific scientific field, it's challenging to acquire unique domain knowledge while keeping the model itself advanced. To address this challenge, a sophisticated large language model system named as Xiwu has been developed, allowing you switch between the most advanced foundation models and quickly teach the model domain knowledge. In this …

abstract advanced art arxiv cs.ai cs.cl cs.lg domain domain knowledge energy hep-ex hep-ph knowledge language language models large language large language models llm llms physics physics.comp-ph scientific sota state type updates

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Lead Data Modeler

@ Sherwin-Williams | Cleveland, OH, United States