Welcome~

Yujia Xie

I am a senior researcher at Microsoft Azure Language Pillars, landing language models to the cloud service. Previously, I work in the Microsoft Azure Cognitive Service Research Team, doing research on the large-scale training of multimodal representation models.

I got my Ph.D. degree from Georgia Tech in 2021, advised by Dr. Hongyuan Zha and Dr. Tuo Zhao. Prior to Ph.D. study, I received a bachelor’s degree in 2016 in theoretic and applied mechanics at Special College of Gifted Young (SCGY), University of Science and Technology of China (USTC).

My research interest lies in the fundamental and practical problems in machine learning, with emphasis on

Selected Publications

Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles 

Shuquan Ye (my intern), Yujia Xie, Dongdong Chen, Yichong Xu, Lu Yuan, Chenguang Zhu, Jing Liao 

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023, PDF

Visual Clues: Bridging Vision and Language Foundations for Image Paragraph Captioning 

Yujia Xie, Luowei Zhou, Xiyang Dai, Lu Yuan, Nguyen Bach, Ce Liu, Michael Zeng 

Advances in Neural Information Processing Systems (NeurIPS) 2022, PDF

REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering 

Yuanze Lin (my intern), Yujia Xie, Dongdong Chen, Yichong Xu, Chenguang Zhu, Lu Yuan 

Advances in Neural Information Processing Systems (NeurIPS) 2022, PDF

A Hypergradient Approach to Robust Regression without Correspondence

Yujia Xie*, Yixiu Mao*, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha

International Conference on Learning Representations (ICLR) 2021, PDF, code

Differentiable Top-k Operator with Optimal Transport

Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

Conference on Neural Information Processing Systems (NeurIPS) 2020, PDF, code, poster

Meta Learning with Relational Information for Short Sequences

Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha

Conference on Neural Information Processing Systems (NeurIPS) 2019, PDF, code, poster

On Scalable and Efficient Computation of Large Scale Optimal Transport

Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

International Conference on Machine Learning (ICML) 2019, PDF, code, poster

A Fast Proximal Point Method for Computing Wasserstein Distance

Yujia Xie, Xiangfeng Wang, Ruijia Wang, Hongyuan Zha

Conference on Uncertainty in Artificial Intelligence (UAI) 2019, PDF, code

Experience

Performed fraud detection using textual data from financial documents. Improved AUC significantly over the traditional method.

Proposed a differentiable and efficient top-k operator, demonstrating significant improvements in image recognition and machine translation.

Proposed a conditional self-attention network for query-based summarization tasks. Achieved improvements in ROUGE score by at least 4.

PhD Research