Cliff Wong

According to our database, Cliff Wong authored at least 18 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Generative Medical Event Models Improve with Scale.

Shane Waxler, Paul Blazek, Davis White, Daniel Sneider, Kevin Chung, Mani Nagarathnam, Patrick Williams, Hank Voeller, Karen Wong, Matthew Swanhorst, Sheng Zhang, Naoto Usuyama, Cliff Wong, Tristan Naumann, Hoifung Poon, Andrew Loza, Daniella Meeker, Seth Hain, Rahul Shah

CoRR, August, 2025

Exploring Scaling Laws for EHR Foundation Models.

Sheng Zhang, Qin Liu, Naoto Usuyama, Cliff Wong, Tristan Naumann, Hoifung Poon

CoRR, May, 2025

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale.

Cliff Wong, Sam Preston, Qianchu Liu, Zelalem Gero, Jass Bagga, Sheng Zhang, Shrey Jain, Theodore Zhao, Yu Gu, Yanbo Xu, Sid Kiblawi, Roshanthi Weerasinghe, Rom S. Leidner, Kristina Young, Brian Piening, Carlo Bifulco, Tristan Naumann, Mu Wei, Hoifung Poon

CoRR, February, 2025

2024

Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging.

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, Ziyi Yang, Hany Hassan Awadalla, Julia Gong, Houdong Hu, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Yu Gu, Cliff Wong, Mu Wei, Tristan Naumann, Muhao Chen, Matthew P. Lungren, Serena Yeung-Levy, Curtis P. Langlotz, Sheng Wang, Hoifung Poon

CoRR, 2024

Foundation Models for Biomedical Image Segmentation: A Survey.

Ho Hin Lee, Yu Gu, Theodore Zhao, Yanbo Xu, Jianwei Yang, Naoto Usuyama, Cliff Wong, Mu Wei, Bennett A. Landman, Yuankai Huo, Alberto Santamaría-Pang, Hoifung Poon

CoRR, 2024

Beyond Clinical Trials: Using Real World Evidence to Investigate Heterogeneous, Time-Varying Treatment Effects.

Isabel Chien, Cliff Wong, Zelalem Gero, Jaspreet Bagga, Risa Ueno, Richard E. Turner, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon, Javier González Hernández

Proceedings of the Machine Learning for Healthcare Conference, 2024

DocLens: Multi-aspect Fine-grained Medical Text Evaluation.

Yiqing Xie, Sheng Zhang, Hao Cheng, Pengfei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, Carolyn P. Rosé

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Enhancing Medical Text Evaluation with GPT-4.

Yiqing Xie, Sheng Zhang, Hao Cheng, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon

CoRR, 2023

TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models.

Javier González Hernández, Cliff Wong, Zelalem Gero, Jass Bagga, Risa Ueno, Isabel Chien, Eduard Oravkin, Emre Kiciman, Aditya V. Nori, Roshanthi Weerasinghe, Rom S. Leidner, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon

CoRR, 2023

Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events.

Yu Gu, Sheng Zhang, Naoto Usuyama, Yonas Woldesenbet, Cliff Wong, Praneeth Sanapathi, Mu Wei, Naveen Valluri, Erika Strandberg, Tristan Naumann, Hoifung Poon

CoRR, 2023

Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing.

Sheng Zhang, Yanbo Xu, Naoto Usuyama, Jaspreet Bagga, Robert Tinn, Sam Preston, Rajesh Rao, Mu Wei, Naveen Valluri, Cliff Wong, Matthew P. Lungren, Tristan Naumann, Hoifung Poon

CoRR, 2023

LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day.

Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology.

Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon

Proceedings of the Machine Learning for Healthcare Conference, 2023

2022

Knowledge-Rich Self-Supervision for Biomedical Entity Linking.

Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Knowledge-Rich Self-Supervised Entity Linking.

Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon

CoRR, 2021

Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature.

Yu Wang, Jinchao Li, Tristan Naumann, Chenyan Xiong, Hao Cheng, Robert Tinn, Cliff Wong, Naoto Usuyama, Richard Rogahn, Zhihong Shen, Yang Qin, Eric Horvitz, Paul N. Bennett, Jianfeng Gao, Hoifung Poon

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Modular Self-Supervision for Document-Level Relation Extraction.

Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2019

Document-Level N-ary Relation Extraction with Multiscale Representation Learning.

Robin Jia, Cliff Wong, Hoifung Poon

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019