Xiaofang Wang

I am a Staff Research Scientist at Meta Superintelligence Labs (MSL), working on multimodal post-training and reasoning. I received my Ph.D. from the Robotics Institute at Carnegie Mellon University and B.S. in Computer Science from Peking University.

E-mail / Google Scholar / LinkedIn

Experience

02/2023 - current: Research Scientist @ Meta Superintelligence Labs

Mutitimodal LLM: Core contributor to Llama 3 & Llama 4
Image Generation: Contributor to Emu 1.0

06/2022 - 02/2023: Research Scientist @ Mobile Vision, Meta Reality Labs
05/2020 - 08/2020: Research Intern @ Google Perception
05/2019 - 08/2019: Research Intern @ Google Cloud AI

Education

08/2017 - 05/2022: Ph.D. in Robotics, Carnegie Mellon University (advisor: Kris Kitani)
08/2015 - 05/2017: M.S. in Robotics, Carnegie Mellon University (advisors: Kris Kitani, Martial Hebert)
08/2011 - 07/2015: B.S. in Computer Science, Peking University

	Cost-Aware Evaluation and Model Scaling for LiDAR-Based 3D Object Detection Xiaofang Wang, Kris M. Kitani International Conference on Robotics and Automation (ICRA), 2023
	Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models Xiaofang Wang, Dan Kondratyuk, Eric Christiansen, Kris M. Kitani, Yair Alon, Elad Eban International Conference on Learning Representations (ICLR), 2022 [Poster] [Google AI Blog]
	Neighborhood-Aware Neural Architecture Search Xiaofang Wang, Shengcao Cao, Mengtian Li, Kris M. Kitani British Machine Vision Conference (BMVC), 2021
	AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification Xiaofang Wang, Xuehan Xiong, Maxim Neumann, AJ Piergiovanni, Michael S. Ryoo, Anelia Angelova, Kris M. Kitani, Wei Hua European Conference on Computer Vision (ECCV), 2020 [Video-1 minute] [Video] [Slides]
	Learnable Embedding Space for Efficient Neural Architecture Compression Shengcao Cao, Xiaofang Wang*, Kris M. Kitani International Conference on Learning Representations (ICLR), 2019* * indicates equal contribution. [Code] [Poster] [Architecture Visualization]
	Error Correction Maximization for Deep Image Hashing Xiang Xu, Xiaofang Wang, Kris M. Kitani British Machine Vision Conference (BMVC), 2018
	Deep Supervised Hashing with Triplet Labels Xiaofang Wang, Yi Shi, Kris M. Kitani Asian Conference on Computer Vision (ACCV), 2016 Oral Presentation, (5.6% acceptance rate) [Code]
	Hamming Compatible Quantization for Hashing Zhe Wang, Ling-Yu Duan, Jie Lin, Xiaofang Wang, Tiejun Huang, Wen Gao International Joint Conference on Artificial Intelligence (IJCAI), 2015