Microsoft Research Lab – Asia
News & features
XGLUE: Expanding cross-lingual understanding and generation with tasks from real-world scenarios
| Nan Duan, Yaobo Liang, and Daniel Campos
What we can teach a model to do with natural language is dictated by the availability of data. Currently, we have a lot of labeled data for very few languages, making it difficult to train models to accomplish question answering,…
Earlier this year, a novel coronavirus rendered online teaching a norm. With “classroom” experiences poor, effective interactions between teachers and students difficult to maintain, and teaching quality easily affected by network conditions, online teaching has created many difficulties for teachers…
He was the first Chinese scholar to become a “complete” fellow at all the following organizations: ACM, AAAI, IEEE, AAAS and IAPR. He was the first Chinese scholar to serve as the program chair of AAAI. He was elected as…
Researchers in Microsoft Research Asia lab launch COVID Insights website
As the COVID-19 pandemic continues to impact communities around the world, researchers everywhere are fighting hard in the hopes of gradually understanding the mystery of the COVID-19 virus through the most advanced technologies available. Based on their expertise and research…
In the news | VentureBeat
Microsoft’s CodeBERT ingests public GitHub repositories to help you find code
Large pretrained language models have improved the state-of-the-art on a range of natural language processing tasks, chiefly because they’re able to learn contextual representations from text without supervision. In a preprint paper, a team of researchers at Microsoft Research Asia used…
Finding the best learning targets automatically: Fully Parameterized Quantile Function for distributional RL
| Li Zhao
Reinforcement learning has achieved great success in game scenarios, with RL agents beating human competitors in such games as Go and poker. Distributional reinforcement learning, in particular, has proven to be an effective approach for training an agent to maximize…
FastSpeech: New text-to-speech model improves on speed, accuracy, and controllability
| Xu Tan
Text to speech (TTS) has attracted a lot of attention recently due to advancements in deep learning. Neural network-based TTS models (such as Tacotron 2, DeepVoice 3 and Transformer TTS) have outperformed conventional concatenative and statistical parametric approaches in terms…
Awards | Association for Computing Machinery (ACM)
Lidong Zhou named 2019 ACM Fellow
Lidong Zhou, Distinguished Scientist, has been named a 2019 ACM Fellow for his contributions to trustworthy distributed computing and to systems research and education in China. The accomplishments of the 2019 ACM Fellows underpin the technologies that define the digital age and…
Getting a better visual: RepPoints detect objects with greater accuracy through flexible and adaptive object modeling
| Han Hu and Steve Lin
Visual understanding tasks are typically centered on objects, such as human pose tracking in Microsoft Kinect and obstacle avoidance in autonomous driving. In the deep learning era, these tasks follow a paradigm where bounding boxes are localized in an image,…