Chen-Yu Lee
Chen-Yu Lee is a research scientist at Google, where he works on machine learning and its real-world applications across various tasks and modalities. Previously, he spent two years at Apple, where he published the Technology Development Group's inaugural research paper at CVPR and launched several key features in ARKit (now Vision Pro). He received his PhD from UC San Diego, advised by Prof. Zhuowen Tu.
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Google
Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization
Cheng-Yu Hsieh
Yung-Sung Chuang
Chun-Liang Li
Abhishek Kumar
James Glass
Alexander Ratner
Ranjay Krishna
2024
Model Swarms: Collaborative Search of Adapted LLM Experts via Swarm Intelligence
Shangbin Feng
Yike Wang
Nathalie Rauschmayr
Yejin Choi
Yulia Tsvetkov
2024
CodecLM: Aligning Language Models with Tailored Synthetic Data
Chun-Liang Li
Jin Miao
NAACL 2024
Chain-of-Table: Evolves Tables in the LLM Reasoning Chain for Table Understanding
Zilong Wang
Hao Zhang
Chun-Liang Li
Jingbo Shang
ICLR (2024)
LMDX: Language Model-based Document Information Extraction And Localization
Kai Kang
Florian Luisier
Xiaoyu Sun
Ramya Sree Boppana
Zilong Wang
Jiaqi Mu
Hao Zhang
Nan Hua
Findings of the Association for Computational Linguistics ACL 2024, Association for Computational Linguistics, Bangkok, Thailand and virtual meeting, pp. 15140-15168
QueryForm: A Simple Zero-shot Form Entity Query Framework
Jacob Devlin
Hao Zhang
Jennifer Dy
ACL (2023)
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Cheng-Yu Hsieh
Chun-Liang Li
Chih-Kuan Yeh
Alexander Ratner
Ranjay Krishna
ACL 2023
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models
Cheng-Yu Hsieh
Si-An Chen
Chun-Liang Li
Alexander Ratner
Ranjay Krishna
arXiv preprint arXiv:2308.00675 (2023)
