Zhao, Ruizhe

1. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
   2024/03/08 by Gemini Robotics Team, Gemini Team, Petko Georgiev +2277 · 4 voices · 763 citations
   Computer Science · #Semantic Web and Ontologies
2. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
   2025/07/07 by Gheorghe Comanici, Comanici, Gheorghe, Eric Bieber +6844 · 8 voices · 1398 citations
   #cs.CL #cs.AI
3. Gemini: A Family of Highly Capable Multimodal Models
   2023/12/19 by Gemini Robotics Team, Gemini Team, Rohan Anil +2692 · 9 voices · 7 citations
   Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Natural Language Processing Techniques #cs.AI #cs.CL #cs.CV
4. Towards Efficient Convolutional Neural Network for Domain-Specific Applications on FPGA
   2018/09/04 by Ruizhe Zhao, Rongxuan Zhao, Ho-Cheung Ng +6 · 1 voice · 1 citation
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #cs.CV
5. Efficient Structured Pruning and Architecture Searching for Group Convolution
   2018/11/23 by Rongxuan Zhao, Wayne Luk, Zhao, Ruizhe +1 · 1 citation
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences
6. Adaptive Loss Scaling for Mixed Precision Training
   2019/10/28 by Rongxuan Zhao, Brian Vogel, Zhao, Ruizhe +3 · 1 citation
   Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications