First Measurement of the Yield of ^8he Isotopes Produced in Liquid Scintillator by Cosmic-Ray Muons at Daya Bay
Physical review D/Physical review D（2024）
Sun Yat-Sen (Zhongshan) University | University of Wisconsin | Brookhaven National Laboratory | National Taiwan University Department of Physics | Institute of High Energy Physics | National United University | Tsinghua University Department of Engineering Physics | North China Electric Power University Institute of High Energy Physics | Siena College | University of California Department of Physics and Astronomy | University of Science and Technology of China | Shandong University | Charles University Faculty of Mathematics and Physics | Joint Institute for Nuclear Research | University of Illinois at Urbana-Champaign Department of Physics | Lawrence Berkeley National Laboratory | Illinois Institute of Technology Department of Physics | Beijing Normal University | Yale University Department of Physics | China Institute of Atomic Energy | Guangxi University | Virginia Tech Center for Neutrino Physics | National Chiao-Tung University Institute of Physics | University of Cincinnati Department of Physics | Temple University Department of Physics | Dongguan University of Technology | University of California Department of Physics | The University of Hong Kong Department of Physics | Nankai University School of Physics | Sun Yat-Sen (Zhongshan) University Institute of High Energy Physics | University of Science and Technology of China Institute of High Energy Physics | Joseph Henry Laboratories Institute of High Energy Physics | The Hong Kong University of Science and Technology Department of Physics | North China Electric Power University | Joseph Henry Laboratories | College of William and Mary | Shanghai Jiao Tong University Department of Physics and Astronomy | Nanjing University | China General Nuclear Power Group | National University of Defense Technology College of Electronic Science and Engineering | Tsinghua University Institute of High Energy Physics | Brookhaven National Laboratory Institute of High Energy Physics | Shandong University Institute of High Energy Physics | Chongqing University | Xi'an Jiaotong University Department of Nuclear Science and Technology
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
