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Embracing the new opportunities and challenges of large foundation models, I'm now more focused on understanding the emergence of intelligence of large language models (LLMs), building LLMs that connect various domains, and constructing personal copilots/assistants for the digital and physical world. Recent News.
2022. Articles 1–20. Microsoft AI, UC Berkeley - Cited by 7,744 - Machine Learning - Computer Vision - Language Models.
Scalabel (pronounced "scalable") is a versatile and scalable annotation platform, supporting both 2D and 3D data labeling. BDD100K, one of the largest driving video datasets, is labeled with this tool. Code repository: https://github.com/scalabel/scalabel.
Xin Wang, Hong Chen, Si'ao Tang, Zihao Wu, Wenwu Zhu. Disentangled Representation Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2024. Paper; Xin Wang,...
Sep 11, 2023 · Xin Wang. Associate Professor. HKUST (Guangzhou) Biography. I am an Associate Professor at the Thrust of Artificial Intelligence, Information Hub, Hong Kong University of Science and Technology (Guangzhou), China.
Xin Wang is an Assistant Professor of Computer Science and Engineering at UC Santa Cruz. He worked at Google AI, Facebook AI Research, Microsoft Research, and Adobe Research....
Quantum AI Research (QuAIR) Lab, led by Prof. Xin Wang at HKUST (Guangzhou), is dedicated to pushing the fundamental boundaries of quantum information processing and driving technological advancements for quantum computing, guided by AI for Quantum and Quantum for AI. Our group is hiring!
Xin Wang, Thomas E. Huang*, Benlin Liu*, Fisher Yu, Xiaolong Wang, Joseph E. Gonzalez, Trevor Darrell International Conference in Computer Vision (ICCV), 2021. Wanderlust: Online Continual Object Detection in the Real World
Xin Wang (Member, IEEE) received the BS degree in information theory and the MS degree in communication and electronic systems from Xidian University, China, in 1994 and 1997, respectively, and the PhD degree in computer science from Shizuoka University, Japan, in 2002.
I am a member of the Computer Vision Group at Microsoft Research in Redmond. My research interest lies at the intersection of computer vision, machine learning and more recently robotics.
