Yifan Xu

Ph.D. Candidate @ UC San Diego

Email: yix081@ucsd.edu

Applied Scientist @ Coinbase

Email: yifan.xu@coinbase.com

Google scholar || Github || Twitter

About Me:

Yifan Xu is currently a Ph.D. Candidate in Cognitive Science at UC San Diego, where he received his B.S. in Computer Science and Engineering. His research, supervised by professor Zhuowen Tu, focuses on the fundamental challenges of artificial intelligence, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. Yifan has been actively publishing his work in top conferences such as CVPR, ICCV, ICLR, and ACL.

Recently, he joined Coinbase to investigate the potential of using AI and blockchain technology together to develop innovative solutions. He is passionate about advancing the field of AI and using it to tackle complex and diverse problems.

In addition to his research, Yifan is also interested in exploring the potential of deep learning and reinforcement learning in trading.

About This Site:

This website content is hosted on the InterPlanetary File System (IPFS), a decentralized network for storing and sharing files. It is backed up by FileCoin, a decentralized storage network that uses a blockchain-based system, through the use of Fleek, a platform for building and deploying websites on IPFS. This setup makes the website more secure and resilient, and enables it to be accessed by a wider audience.

My DNS (Centralized) URL: yfxu.com
My ENS (Decentralized) Address: yfxu.eth.limo

Publication

* indicates equal contribution

• Blockchain

• "Detection of Malicious On-Chain Programs", Y Xu, George Liu, I Rustandi, Y MA United States Patent

• Reinforcement Learning

• "On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning", Y Xu*, N Hansen*, Z Wang, YC Chan, H Su, Z Tu, ICLR 2023
• "Neural Program Synthesis By Self-Learning", Y Xu*, L Dai*, U Singh, K Zhang, Z Tu, arXiv preprint

• Computer Vision

• "Co-scale conv-attentional image transformers", W Xu*, Y Xu*, T Chang, Z Tu, ICCV 2021 (Oral)
• "Line Segment Detection Using Transformers without Edges", Y Xu*, W Xu*, D Cheung, Z Tu, CVPR 2021 (Oral)
• "Pose Recognition with Cascade Transformers", K Li, S Wang, X Zhang, Y Xu, W Xu, Z Tu, CVPR 2021
• "Attentional Constellation Nets for Few-Shot Learning", W Xu*, Y Xu*, H Wang*, Z Tu, ICLR 2021
• "Guided variational autoencoder for disentanglement learning", Z Ding*, Y Xu*, W Xu, G Parmar, Y Yang, M Welling, Z Tu, CVPR 2020

• Nature Language Processing

• "Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models", TA Chang, Y Xu, W Xu, Z Tu, ACL 2021
• "Rethinking exposure bias in language modeling", Y Xu*, K Zhang*, H Dong, Y Sun, W Zhao, Z Tu, arXiv preprint