Document-Level N-ary Relation Extraction with Multiscale Representation Learning. - Robin Jia; Cliff Wong; Hoifung Poon (NAACL-HLT (1), 2019)

Modular Self-Supervision for Document-Level Relation Extraction. - Sheng Zhang 012; Cliff Wong; Naoto Usuyama; Sarthak Jain; Tristan Naumann; Hoifung Poon (EMNLP (1), 2021)

Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. - Yu Wang 009; Jinchao Li; Tristan Naumann; Chenyan Xiong; Hao Cheng 002; Robert Tinn; Cliff Wong; Naoto Usuyama; Richard Rogahn; Zhihong Shen; Yang Qin; Eric Horvitz; et al. (KDD, 2021)

Knowledge-Rich Self-Supervised Entity Linking. - Sheng Zhang 012; Hao Cheng 002; Shikhar Vashishth; Cliff Wong; Jinfeng Xiao; Xiaodong Liu 003; Tristan Naumann; Jianfeng Gao 001; Hoifung Poon (CoRR, 2021)

Knowledge-Rich Self-Supervision for Biomedical Entity Linking. - Sheng Zhang 012; Hao Cheng 002; Shikhar Vashishth; Cliff Wong; Jinfeng Xiao; Xiaodong Liu 003; Tristan Naumann; Jianfeng Gao 001; Hoifung Poon (EMNLP (Findings), 2022)

Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. - Cliff Wong; Sheng Zhang 012; Yu Gu 017; Christine Moung; Jacob Abel; Naoto Usuyama; Roshanthi Weerasinghe; Brian Piening; Tristan Naumann; Carlo Bifulco; Hoifung Poon (MLHC, 2023)

LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. - Chunyuan Li; Cliff Wong; Sheng Zhang 012; Naoto Usuyama; Haotian Liu; Jianwei Yang; Tristan Naumann; Hoifung Poon; Jianfeng Gao 001 (NeurIPS, 2023)

Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing. - Sheng Zhang 012; Yanbo Xu; Naoto Usuyama; Jaspreet Bagga; Robert Tinn; Sam Preston; Rajesh Rao; Mu Wei; Naveen Valluri; Cliff Wong; Matthew P. Lungren; Tristan Naumann; et al. (CoRR, 2023)

Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events. - Yu Gu 017; Sheng Zhang 012; Naoto Usuyama; Yonas Woldesenbet; Cliff Wong; Praneeth Sanapathi; Mu Wei; Naveen Valluri; Erika Strandberg; 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; et al. (CoRR, 2023)

Enhancing Medical Text Evaluation with GPT-4. - Yiqing Xie; Sheng Zhang 012; Hao Cheng 002; Zelalem Gero; Cliff Wong; Tristan Naumann; Hoifung Poon (CoRR, 2023)

DocLens: Multi-aspect Fine-grained Medical Text Evaluation. - Yiqing Xie; Sheng Zhang 012; Hao Cheng 002; Pengfei Liu; Zelalem Gero; Cliff Wong; Tristan Naumann; Hoifung Poon; Carolyn P. Rosé (ACL (1), 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 (MLHC, 2024)

Foundation Models for Biomedical Image Segmentation: A Survey. - Ho Hin Lee; Yu Gu 017; Theodore Zhao; Yanbo Xu; Jianwei Yang; Naoto Usuyama; Cliff Wong; Mu Wei; Bennett A. Landman; Yuankai Huo; Alberto Santamaría-Pang; Hoifung Poon (CoRR, 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 012; Fei Wang 060; Yujia Xie; Mahmoud Khademi; Ziyi Yang; Hany Hassan Awadalla; Julia Gong; et al. (CoRR, 2024)

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale. - Cliff Wong; Sam Preston; Qianchu Liu; Zelalem Gero; Jass Bagga; Sheng Zhang 012; Shrey Jain; Theodore Zhao; Yu Gu 017; Yanbo Xu; Sid Kiblawi; Roshanthi Weerasinghe; et al. (CoRR, 2025)

Exploring Scaling Laws for EHR Foundation Models. - Sheng Zhang 012; Qin Liu 010; Naoto Usuyama; Cliff Wong; Tristan Naumann; Hoifung Poon (CoRR, 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 012; Naoto Usuyama; et al. (CoRR, 2025)