I am a Principal Researcher at Microsoft Research. My recent research focuses on large-scale natural language processing and multimodal learning, which includes:

• Building (multimodal) foundation models and vision-language assistant [1, 2, 3]
• LLM distillation for broad application classes [4, 5]
• Domain adaptation of LLMs without specialized training [6, 7]

If you are interested in working with me on any of these topics, please feel free to drop me an email.

I obtained my Ph.D. in natural language processing and machine learning at Johns Hopkins University, advised by Benjamin Van Durme and Kevin Duh. My PhD research studies transductive semantic parsing. My work has been nominated for the best paper of ACL. I have served as an Area Chair for NeurIPS, EMNLP, NAACL, AAAI & IJCNLP-AACL.

Tutorials

• Precision Health in the Age of Large Language Models KDD 2023
  Hoifung Poon, Tristan Naumann, Sheng Zhang, Javier González
  [ Webpage | Blog ]

Recent Publications [Google Scholar]

• A whole-slide foundation model for digital pathology from real-world data Nature
  Hanwen Xu^*, Naoto Usuyama^*, Jaspreet Bagga, Sheng Zhang, Rajesh Rao, Tristan Naumann, Cliff Wong, Zelalem Gero, Javier González, Yu Gu, Yanbo Xu, Mu Wei, Wenhui Wang, Shuming Ma, Furu Wei, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Jaylen Rosemon, Tucker Bower, Soohee Lee, Roshanthi Weerasinghe, Bill J. Wright, Ari Robicsek, Brian Piening, Carlo Bifulco, Sheng Wang, Hoifung Poon
  (^*equal contribution)
  [ Data | Model ]
• 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
  (^*equal contribution)
  [ CheXprompt ]
• DocLens: Multi-aspect Fine-grained Evaluation for Medical Text Generation ACL 2024
  Yiqing Xie, Sheng Zhang, Hao Cheng, Pengfei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, Carolyn Rose
  [ DocLens ]
• Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
  Harsha Nori^*, Yin Tat Lee^*, Sheng Zhang^*, Dean Carignan, Richard Edgar, Nicolo Fusi, Nicholas King, Jonathan Larson, Yuanzhi Li, Weishung Liu, Renqian Luo, Scott Mayer McKinney, Robert Osazuwa Ness, Hoifung Poon, Tao Qin, Naoto Usuyama, Chris White, Eric Horvitz
  (^*equal contribution)
  [ MSR blog | promptbase ]
• UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition ICLR 2024
  Wenxuan Zhou^*, Sheng Zhang^*, Yu Gu, Muhao Chen, Hoifung Poon (^*equal contribution)
  [ Demo | Model | MSR Podcast ]
• LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day NeurIPS 2023 Datasets & Benchmarks (Spotlight)
  Chunyuan Li^*, Cliff Wong^*, Sheng Zhang^*, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao (^*equal contribution)
  [ Project page ]
• 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 (^*equal contribution)
  [ Model ]
• BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys
  Yu Gu^*, Jianwei Yang^*, Naoto Usuyama, Chunyuan Li, Sheng Zhang, Matthew P. Lungren, Jianfeng Gao, Hoifung Poon (^*equal contribution)
  [ Project page ]

Click for full publications

• Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries
  Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
• T-Rex: Text-assisted Retrosynthesis Prediction
  Yifeng Liu, Hanwen Xu, Tangqi Fang, Haocheng Xi, Zixuan Liu, Sheng Zhang, Hoifung Poon, Sheng Wang
• Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology MLHC 2023
  Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
• 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
• Context-faithful Prompting for Large Language Models EMNLP 2023 (Findings)
  Wenxuan Zhou, Sheng Zhang, Hoifung Poon, Muhao Chen
  [ Code ]
• Compositional Zero-Shot Domain Transfer with Text-to-Text Models TACL 2023
  Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland
• Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning ICLR 2023
  Sheng Zhang, Hao Cheng, Jianfeng Gao, Hoifung Poon
  [ Code ]
• Continual Contrastive Finetuning Improves Low-Resource Relation Extraction ACL 2023
  Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon
• BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining Briefings in Bioinformatics
  Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu
  [ Code ]
• Knowledge-Rich Self-Supervision for Biomedical Entity Linking EMNLP 2022 (Findings)
  Sheng Zhang^*, Hao Cheng^*, Shikhar Vashishth^*, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon (^*equal contribution)
  [ Code ]
• Modular Self-Supervision for Document-Level Relation Extraction EMNLP 2021
  Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon
• Joint Universal Syntactic and Semantic Parsing TACL 2021
  Elias Stengel-Eskin, Kenton Murray, Sheng Zhang, Aaron Steven White, Benjamin Van Durme
  [ Code ]
• Universal Decompositional Semantic Parsing ACL 2020
  Elias Stengel-Eskin, Aaron Steven White, Sheng Zhang, Benjamin Van Durme
  [ Decomp | BibTex ]
• Transductive Semantic Parsing Doctoral Dissertation
  Sheng Zhang
• The Universal Decompositional Semantics Dataset and Decomp Toolkit LREC 2020
  Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha, Venkata Govindarajan, Dee Ann Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Francis Ferraro, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme
  [ Decomp | BibTex ]
• Broad-Coverage Semantic Parsing as Transduction EMNLP 2019
  Sheng Zhang, Xutai Ma, Kevin Duh, Benjamin Van Durme
  [ BibTex ]
• AMR Parsing as Sequence-to-Graph Transduction ACL 2019  Best Paper Nominee 
  Sheng Zhang, Xutai Ma, Kevin Duh, Benjamin Van Durme
  [ Code | BibTex ]
• ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension
  Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, Benjamin Van Durme
  [ LeaderBoard ]
• Deep Generalized Canonical Correlation Analysis RepL4NLP at ACL 2019
  Adrian Benton, Huda Khayrallah, Biman Gujral, Dee Ann Reisinger, Sheng Zhang, Raman Arora
  [ Code | BibTex ]
• Unsupervised Deep Structured Semantic Models for Commonsense Reasoning NAACL 2019
  Shuohang Wang, Sheng Zhang, Yelong Shen, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Jing Jiang
  [ BibTex ]
• Cross-lingual Decompositional Semantic Parsing EMNLP 2018
  Sheng Zhang, Xutai Ma, Rachel Rudinger, Kevin Duh, Benjamin Van Durme
  [ Supplements | BibTex ]
• Neural Davidsonian Semantic Proto-role Labeling EMNLP 2018
  Rachel Rudinger, Adam Teichert, Ryan Culkin, Sheng Zhang, Benjamin Van Durme
  [ BibTex ]
• Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds ^*SEM 2018
  Sheng Zhang, Kevin Duh, Benjamin Van Durme
  [ Code | BibTex ]
• Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction ^*SEM 2018
  Hongyuan Mei^*, Sheng Zhang^*, Kevin Duh, Benjamin Van Durme (^*equal contribution)
  [ BibTex ]
• Selective Decoding for Cross-lingual Open Information Extraction IJCNLP 2017
  Sheng Zhang, Kevin Duh, Benjamin Van Durme
  [ BibTex ]
• An Evaluation of PredPatt and Open IE via Stage 1 Semantic Role Labeling IWCS 2017
  Sheng Zhang, Rachel Rudinger, Kevin Duh, Benjamin Van Durme
  [ Code | BibTex ]
• MT/IE: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models EACL 2017
  Sheng Zhang, Kevin Duh, Benjamin Van Durme
  [ Code | Slides | BibTex ]
• Ordinal Common-sense Inference TACL 2017
  Sheng Zhang, Kevin Duh, Benjamin Van Durme
  [ Corpus | Examples | Slides | BibTex ]
• Universal Decompositional Semantics on Universal Dependencies EMNLP 2016
  Aaron Steven White, Dee Ann Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme
  [ Project Page | BibTex ]
• Semantic Interpretation of Superlative Expressions via Structured Knowledge Bases ACL 2015
  Sheng Zhang, Yansong Feng, Songfang Huang, Kun Xu, Zhe Han, Dongyan Zhao
  [ BibTex ]
• What Is the Longest River in the USA? Semantic Parsing for Aggregation Questions AAAI 2015
  Kun Xu, Sheng Zhang, Yansong Feng, Dongyan Zhao
  [ BibTex ]
• Answering Natural Language Questions via Phrasal Semantic Parsing NLPCC 2014
  Kun Xu, Sheng Zhang, Yansong Feng, Dongyan Zhao
  [ BibTex ]

Service

• Area Chair: NeurIPS 2023; ARR; ACL 2024; NAACL 2021, 2024; EMNLP 2022; IJCNLP-AACL 2023
• Tutorial: KDD 2023
• Organizer: Workshop on COmmonsense INference in NLP (COIN) at EMNLP 2019
• (S)PC Member/Reviewer: TACL; Computational Linguistics; ARR; BMC Bioinformatics; ACL 2017-2023; EMNLP 2018-2021; AAAI 2020-2024; ICCV 2023; NAACL 2018-2021; EACL 2017 2021; AACL-IJCNLP 2020; COLM 2024; COLING 2020; CoNLL 2019; IJCNLP 2017; IWCS 2017; NLE