"All truths are easy to understand once they are discovered; the point is to discover them."
About Me
Yifan Xu is currently an Applied Scientist at Coinbase, where he investigates the potential of using AI and blockchain technology together to develop innovative solutions. He is also working on large language models as part of his ongoing research. Yifan is passionate about advancing the field of AI and using it to tackle complex and diverse problems. In addition to his work at Coinbase, Yifan is interested in exploring the potential of deep learning and reinforcement learning in trading.
Before joining Coinbase, Yifan completed his Ph.D. in Cognitive Science at UC San Diego, where he also received his B.S. in Computer Science and Engineering. Under the supervision of Professor Zhuowen Tu, his research is centered around addressing the intricate complexities within several domains of artificial intelligence, such as machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. Yifan has published his work in top conferences such as ICLR, CVPR, ICCV, and ACL.
Tweets by yfxu_ethAbout This Site
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My ENS (Decentralized) Address: yfxu.eth.limo
Publication
* indicates equal contribution
Blockchain
- "Detection of Malicious On-Chain Programs", held by Coinbase and authored by 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
Services
Organizer
- I helped plan the Machine Learning and Blockchain Summit at Coinbase. This is the first summit of its kind, bringing together experts in both machine learning and blockchain technology. We look forward to welcoming you at next year's event!
Reviewer