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
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
Chain-of-Table: Evolves Tables in the LLM Reasoning Chain for Table Understanding
Zilong Wang
Hao Zhang
Chun-Liang Li
Jingbo Shang
ICLR (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
FormNetV2: Inductive Multimodal Graph Contrastive Learning for Form Document Information Extraction
Chun-Liang Li
Hao Zhang
Xiang Zhang
Kihyuk Sohn
Nikolai Glushnev
Joshua Ainslie
Nan Hua
ACL (2023)
VRDU: A Benchmark for Visually-rich Document Understanding
Zilong Wang
Wei Wei
2023 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
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
