Zifeng Wang
Zifeng Wang is a research scientist at Google, working on exciting machine learning algorithms and their applications. His research interests include efficient model adaptation, continual learning, and large language models. He received his PhD in machine learning from Northeastern University advised by Prof. Jennifer Dy.
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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
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)
Model Swarms: Collaborative Search of Adapted LLM Experts via Swarm Intelligence
Shangbin Feng
Yike Wang
Nathalie Rauschmayr
Yejin Choi
Yulia Tsvetkov
2024
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
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL
Satya Gundabathula
Hanjun Dai
TMLR (2024)
QueryForm: A Simple Zero-shot Form Entity Query Framework
Jacob Devlin
Hao Zhang
Jennifer Dy
ACL (2023)
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning
Han Zhang
Xiaoqi Ren
Jennifer Dy
ECCV 2022
Learning to prompt for continual learning
Han Zhang
Xiaoqi Ren
Jennifer Dy
CVPR2022
