Category google-researches
Deep Learning with Label Differential Privacy
Image-Text Pre-training with Contrastive Captioners
Vector-Quantized Image Modeling with Improved VQGAN
Posted by Jiahui Yu, Senior Research Scientist, and Jing Yu Koh, Research Software Engineer, Google Research In recent years, natural language processing models have dramatically improved their ability to learn general-purpose representations, which has resulted in significant performance gains for…
Contextual Rephrasing in Google Assistant
Challenges in Multi-objective Optimization for Automatic Wireless Network Planning
Posted by Sara Ahmadian and Matthew Fahrbach, Research Scientists, Google Research, Large-Scale Optimization Team Economics, combinatorics, physics, and signal processing conspire to make it difficult to design, build, and operate high-quality, cost-effective wireless networks. The radio transceivers that communicate with…
Language Models Perform Reasoning via Chain of Thought
Unlocking Zero-Resource Machine Translation to Support New Languages in Google Translate
Learning Locomotion Skills Safely in the Real World
Posted by Jimmy (Tsung-Yen) Yang, Student Researcher, Robotics at Google The promise of deep reinforcement learning (RL) in solving complex, high-dimensional problems autonomously has attracted much interest in areas such as robotics, game playing, and self-driving cars. However, effectively training…
GraphWorld: Advances in Graph Benchmarking
John Palowitch and Anton Tsitsulin, Research Scientists, Google Research, Graph Mining team Graphs are very common representations of natural systems that have connected relational components, such as social networks, traffic infrastructure, molecules, and the internet. Graph neural networks (GNNs) are…