Cycle Cover Ratio of Regular Matroids. - Hong-Jian Lai; Hoifung Poon (Eur. J. Comb., 2002)

Upper Bounds of Dynamic Chromatic Number. - Hong-Jian Lai; Bruce Montgomery; Hoifung Poon (Ars Comb., 2003)

Spanning Trails Connecting Given Edges. - Hong-Jian Lai; Xiangwen Li; Hoifung Poon; Yongbin Ou (Graphs Comb., 2005)

Nowhere zero 4-flow in regular matroids. - Hong-Jian Lai; Xiangwen Li; Hoifung Poon (J. Graph Theory, 2005)

Unifying Logical and Statistical AI. - Pedro M. Domingos; Stanley Kok; Hoifung Poon; Matthew Richardson; Parag Singla (AAAI, 2006)

Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. - Hoifung Poon; Pedro M. Domingos (AAAI, 2006)

Joint Inference in Information Extraction. - Hoifung Poon; Pedro M. Domingos (AAAI, 2007)

A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC. - Hoifung Poon; Pedro M. Domingos; Marc Sumner (AAAI, 2008)

Joint Unsupervised Coreference Resolution with Markov Logic. - Hoifung Poon; Pedro M. Domingos (EMNLP, 2008)

Markov Logic. - Pedro M. Domingos; Stanley Kok; Daniel Lowd; Hoifung Poon; Matthew Richardson; Parag Singla (Probabilistic Inductive Logic Programming, 2008)

Just Add Weights: Markov Logic for the Semantic Web. - Pedro M. Domingos; Daniel Lowd; Stanley Kok; Hoifung Poon; Matthew Richardson; Parag Singla (URSW (LNCS Vol.), 2008)

Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. - Pedro M. Domingos; Stanley Kok; Daniel Lowd; Hoifung Poon; Matthew Richardson; Parag Singla; Marc Sumner; Jue Wang (SSPR/SPR, 2008)

Language ID in the Context of Harvesting Language Data off the Web. - Fei Xia 004; William D. Lewis; Hoifung Poon (EACL, 2009)

Unsupervised Semantic Parsing. - Hoifung Poon; Pedro M. Domingos (EMNLP, 2009)

Unsupervised Morphological Segmentation with Log-Linear Models. - Hoifung Poon; Colin Cherry; Kristina Toutanova (HLT-NAACL, 2009)

Markov Logic: A Language and Algorithms for Link Mining. - Pedro M. Domingos; Daniel Lowd; Stanley Kok; Aniruddh Nath; Hoifung Poon; Matthew Richardson; Parag Singla (Link Mining, 2010)

Machine Reading: A "Killer App" for Statistical Relational AI. - Hoifung Poon; Pedro M. Domingos (StarAI@AAAI, 2010)

Unsupervised Ontology Induction from Text. - Hoifung Poon; Pedro M. Domingos (ACL, 2010)

Markov Logic in Natural Language Processing: Theory, Algorithms, and Applications. - Hoifung Poon (NAACL (Tutorial Abstracts), 2010)

Joint Inference for Knowledge Extraction from Biomedical Literature. - Hoifung Poon; Lucy Vanderwende (HLT-NAACL, 2010)

Sum-Product Networks: A New Deep Architecture. - Hoifung Poon; Pedro M. Domingos (UAI, 2011)

Unsupervised semantic parsing. - Hoifung Poon (MLSLP, 2012)

Grounded Unsupervised Semantic Parsing. - Hoifung Poon (ACL (1), 2013)

Probabilistic Frame Induction. - Jackie Chi Kit Cheung; Hoifung Poon; Lucy Vanderwende (HLT-NAACL, 2013)

Literome: PubMed-scale genomic knowledge base in the cloud. - Hoifung Poon; Chris Quirk; Charlie DeZiel; David Heckerman (Bioinform., 2014)

Model Selection for Type-Supervised Learning with Application to POS Tagging. - Kristina Toutanova; Waleed Ammar; Pallavi Choudhury; Hoifung Poon (CoNLL, 2015)

Representing Text for Joint Embedding of Text and Knowledge Bases. - Kristina Toutanova; Danqi Chen 001; Patrick Pantel; Hoifung Poon; Pallavi Choudhury; Michael Gamon (EMNLP, 2015)

Grounded Semantic Parsing for Complex Knowledge Extraction. - Ankur P. Parikh; Hoifung Poon; Kristina Toutanova (HLT-NAACL, 2015)

Distant Supervision for Cancer Pathway Extraction from Text. - Hoifung Poon; Kristina Toutanova; Chris Quirk (Pacific Symposium on Biocomputing, 2015)

Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text. - Kristina Toutanova; Xi Victoria Lin; Wen-tau Yih; Hoifung Poon; Chris Quirk (ACL (1), 2016)

Unifying Logical and Statistical AI. - Pedro M. Domingos; Daniel Lowd; Stanley Kok; Aniruddh Nath; Hoifung Poon; Matthew Richardson; Parag Singla (LICS, 2016)

NLP for Precision Medicine. - Hoifung Poon; Chris Quirk; Kristina Toutanova; Wen-tau Yih (ACL (Tutorial Abstracts), 2017)

Distant Supervision for Relation Extraction beyond the Sentence Boundary. - Chris Quirk; Hoifung Poon (EACL (1), 2017)

Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach. - Emmanouil A. Platanios; Hoifung Poon; Tom M. Mitchell; Eric Horvitz (NIPS, 2017)

EZLearn: Exploiting Organic Supervision in Large-Scale Data Annotation. - Maxim Grechkin; Hoifung Poon; Bill Howe (CoRR, 2017)

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. - Tarek R. Besold; Artur S. d'Avila Garcez; Sebastian Bader 001; Howard Bowman; Pedro M. Domingos; Pascal Hitzler; Kai-Uwe Kühnberger; Luís C. Lamb; Daniel Lowd; Priscila Machado Vieira Lima; Leo de Penning; Gadi Pinkas; et al. (CoRR, 2017)

Cross-Sentence N-ary Relation Extraction with Graph LSTMs. - Nanyun Peng 001; Hoifung Poon; Chris Quirk; Kristina Toutanova; Wen-tau Yih (Trans. Assoc. Comput. Linguistics, 2017)

Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision. - Hai Wang; Hoifung Poon (EMNLP, 2018)

EZLearn: Exploiting Organic Supervision in Automated Data Annotation. - Maxim Grechkin; Hoifung Poon; Bill Howe (IJCAI, 2018)

DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain. - Yichong Xu; Xiaodong Liu 003; Chunyuan Li; Hoifung Poon; Jianfeng Gao 001 (BioNLP@ACL, 2019)

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

Augmenting subnetwork inference with information extracted from the scientific literature. - Sid Kiblawi; Deborah Chasman; Amanda Henning; Eunju Park; Hoifung Poon; Michael Gould; Paul Ahlquist; Mark Craven (PLoS Comput. Biol., 2019)

The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding. - Xiaodong Liu 003; Yu Wang 009; Jianshu Ji; Hao Cheng 002; Xueyun Zhu; Emmanuel Awa; Pengcheng He; Weizhu Chen; Hoifung Poon; Guihong Cao; Jianfeng Gao 001 (ACL (demo), 2020)

Adversarial Training for Large Neural Language Models. - Xiaodong Liu 003; Hao Cheng 002; Pengcheng He; Weizhu Chen; Yu Wang 009; Hoifung Poon; Jianfeng Gao 001 (CoRR, 2020)

CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search. - Chenyan Xiong; Zhenghao Liu 001; Si Sun; Zhuyun Dai; Kaitao Zhang; Shi Yu 001; Zhiyuan Liu 001; Hoifung Poon; Jianfeng Gao 001; Paul Bennett 001 (CoRR, 2020)

Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic. - Hunter Lang; Hoifung Poon (AAAI, 2021)

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)

Targeted Adversarial Training for Natural Language Understanding. - Lis Pereira; Xiaodong Liu 003; Hao Cheng 002; Hoifung Poon; Jianfeng Gao 001; Ichiro Kobayashi (NAACL-HLT, 2021)

Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. - Hoifung Poon; Hai Wang; Hunter Lang (CoRR, 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)

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. - Tarek R. Besold; Artur S. d'Avila Garcez; Sebastian Bader 001; Howard Bowman; Pedro M. Domingos; Pascal Hitzler; Kai-Uwe Kühnberger; Luís C. Lamb; Priscila Machado Vieira Lima; Leo de Penning; Gadi Pinkas; Hoifung Poon; et al. (Neuro-Symbolic Artificial Intelligence, 2021)

Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. - Hoifung Poon; Hai Wang; Hunter Lang (Neuro-Symbolic Artificial Intelligence, 2021)

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. - Benedikt Boecking; Naoto Usuyama; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Stephanie L. Hyland; Maria Wetscherek; Tristan Naumann; Aditya V. Nori; Javier Alvarez-Valle; Hoifung Poon; Ozan Oktay (ECCV (36), 2022)

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)

Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision. - Sam Preston; Mu Wei; Rajesh Rao; Robert Tinn; Naoto Usuyama; Michael Lucas; Roshanthi Weerasinghe; Soohee Lee; Brian Piening; Paul Tittel; Naveen Valluri; Tristan Naumann; et al. (CoRR, 2022)

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. - Yu Gu 017; Robert Tinn; Hao Cheng 002; Michael Lucas; Naoto Usuyama; Xiaodong Liu 003; Tristan Naumann; Jianfeng Gao 001; Hoifung Poon (ACM Trans. Comput. Heal., 2022)

BioGPT: generative pre-trained transformer for biomedical text generation and mining. - Renqian Luo; Liai Sun; Yingce Xia; Tao Qin 001; Sheng Zhang 012; Hoifung Poon; Tie-Yan Liu (Briefings Bioinform., 2022)

Interactive Span Recommendation for Biomedical Text. - Louis Blankemeier; Theodore Zhao; Robert Tinn; Sid Kiblawi; Yu Gu 017; Akshay Chaudhari; Hoifung Poon; Sheng Zhang 012; Mu Wei; Joseph Preston (ClinicalNLP@ACL, 2023)

Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. - Wenxuan Zhou; Sheng Zhang 012; Tristan Naumann; Muhao Chen 001; Hoifung Poon (ACL (1), 2023)

Exploring the Boundaries of GPT-4 in Radiology. - Qianchu Liu; Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Maria Wetscherek; Robert Tinn; Harshita Sharma; Fernando Pérez-García; Anton Schwaighofer; Pranav Rajpurkar; Sameer Tajdin Khanna; et al. (EMNLP, 2023)

Context-faithful Prompting for Large Language Models. - Wenxuan Zhou; Sheng Zhang 012; Hoifung Poon; Muhao Chen 001 (EMNLP (Findings), 2023)

Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning. - Sheng Zhang 012; Hao Cheng 002; Jianfeng Gao 001; Hoifung Poon (ICLR, 2023)

Precision Health in the Age of Large Language Models. - Hoifung Poon; Tristan Naumann; Sheng Zhang 012; Javier González Hernández (KDD, 2023)

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)

BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction. - Cai Yang; Addie Woicik; Hoifung Poon; Sheng Wang (CoRR, 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)

Self-Verification Improves Few-Shot Clinical Information Extraction. - Zelalem Gero; Chandan Singh; Hao Cheng 002; Tristan Naumann; Michel Galley; Jianfeng Gao 001; Hoifung Poon (CoRR, 2023)

Automatic Calibration and Error Correction for Large Language Models via Pareto Optimal Self-Supervision. - Theodore Zhao; Mu Wei; J. Samuel Preston; Hoifung Poon (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)

BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys. - Yu Gu 017; Jianwei Yang; Naoto Usuyama; Chunyuan Li; Sheng Zhang 012; Matthew P. Lungren; Jianfeng Gao 001; 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)

Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. - Harsha Nori; Yin Tat Lee; Sheng Zhang 012; Dean Carignan; Richard Edgar; Nicolò Fusi; Nicholas King; Jonathan Larson; Yuanzhi Li; Weishung Liu; Renqian Luo; Scott Mayer McKinney; et al. (CoRR, 2023)

When an Image is Worth 1, 024 x 1, 024 Words: A Case Study in Computational Pathology. - Wenhui Wang 003; Shuming Ma; Hanwen Xu; Naoto Usuyama; Jiayu Ding; Hoifung Poon; Furu Wei (CoRR, 2023)

Compositional Zero-Shot Domain Transfer with Text-to-Text Models. - Fangyu Liu 001; Qianchu Liu; Shruthi Bannur; Fernando Pérez-García; Naoto Usuyama; Sheng Zhang 012; Tristan Naumann; Aditya V. Nori; Hoifung Poon; Javier Alvarez-Valle; Ozan Oktay; Stephanie L. Hyland (Trans. Assoc. Comput. Linguistics, 2023)

Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. - Sam Preston; Mu Wei; Rajesh Rao; Robert Tinn; Naoto Usuyama; Michael Lucas; Yu Gu 017; Roshanthi Weerasinghe; Soohee Lee; Brian Piening; Paul Tittel; Naveen Valluri; et al. (Patterns, 2023)

Fine-tuning large neural language models for biomedical natural language processing. - Robert Tinn; Hao Cheng 002; Yu Gu 017; Naoto Usuyama; Xiaodong Liu 003; Tristan Naumann; Jianfeng Gao 001; Hoifung Poon (Patterns, 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)

Pareto Optimal Learning for Estimating Large Language Model Errors. - Theodore Zhao; Mu Wei; Joseph Preston; Hoifung Poon (ACL (1), 2024)

Cautionary Tales on Synthetic Controls in Survival Analyses. - Alicia Curth; Hoifung Poon; Aditya V. Nori; Javier González 002 (CLeaR, 2024)

mDPO: Conditional Preference Optimization for Multimodal Large Language Models. - Fei Wang 060; Wenxuan Zhou; James Y. Huang; Nan Xu; Sheng Zhang 012; Hoifung Poon; Muhao Chen 001 (EMNLP, 2024)

UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition. - Wenxuan Zhou; Sheng Zhang 012; Yu Gu 017; Muhao Chen 001; Hoifung Poon (ICLR, 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)

T-Rex: Text-assisted Retrosynthesis Prediction. - Yifeng Liu 004; Hanwen Xu; Tangqi Fang; Haocheng Xi; Zixuan Liu 001; Sheng Zhang 012; Hoifung Poon; Sheng Wang 012 (CoRR, 2024)

Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries. - Zelalem Gero; Chandan Singh; Yiqing Xie; Sheng Zhang 012; Tristan Naumann; Jianfeng Gao 001; 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)

BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once. - Theodore Zhao; Yu Gu 017; Jianwei Yang; Naoto Usuyama; Ho Hin Lee; Tristan Naumann; Jianfeng Gao 001; Angela Crabtree; Jacob Abel; Christine Moung; Brian Piening; Carlo Bifulco; et al. (CoRR, 2024)

MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging. - Noel C. F. Codella; Ying Jin; Shrey Jain; Yu Gu; Ho Hin Lee; Asma Ben Abacha; Alberto Santamaría-Pang; Will Guyman; Naiteek Sangani; Sheng Zhang; Hoifung Poon; Stephanie L. Hyland; et al. (CoRR, 2024)

A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges. - Zifeng Wang 008; Hanyin Wang; Benjamin P. Danek; Ying Li; Christina Mack; Hoifung Poon; Yajuan Wang; Pranav Rajpurkar; Jimeng Sun 001 (CoRR, 2024)

Boltzmann Attention Sampling for Image Analysis with Small Objects. - Theodore Zhao; Sid Kiblawi; Naoto Usuyama; Ho Hin Lee; Sam Preston; Hoifung Poon; Mu Wei (CVPR, 2025)

MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding. - Fei Wang 060; Xingyu Fu; James Y. Huang; Zekun Li 007; Qin Liu 010; Xiaogeng Liu; Mingyu Derek Ma; Nan Xu; Wenxuan Zhou; Kai Zhang 008; Tianyi Lorena Yan; Wenjie Jacky Mo; et al. (ICLR, 2025)

From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning. - Nan Xu; Fei Wang 060; Sheng Zhang 012; Hoifung Poon; Muhao Chen 001 (NAACL (Long Papers), 2025)

A perspective for adapting generalist AI to specialized medical AI applications and their challenges. - Zifeng Wang 008; Hanyin Wang; Benjamin P. Danek; Ying Li; Christina Mack; Luk Arbuckle; Devyani Biswal; Hoifung Poon; Yajuan Wang; Pranav Rajpurkar; Cao Xiao; Jimeng Sun 001 (npj Digit. Medicine, 2025)

Offset Unlearning for Large Language Models. - James Y. Huang; Wenxuan Zhou; Fei Wang 060; Fred Morstatter; Sheng Zhang 012; Hoifung Poon; Muhao Chen 001 (Trans. Mach. Learn. Res., 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 012; Shrey Jain; Theodore Zhao; Yu Gu 017; Yanbo Xu; Sid Kiblawi; Roshanthi Weerasinghe; et al. (CoRR, 2025)

Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning. - Sheng Zhang 012; Qianchu Liu; Guanghui Qin; Tristan Naumann; Hoifung Poon (CoRR, 2025)

Semantic-Clipping: Efficient Vision-Language Modeling with Semantic-Guidedd Visual Selection. - Bangzheng Li; Fei Wang 060; Wenxuan Zhou; Nan Xu; Ben Zhou; Sheng Zhang 012; Hoifung Poon; Muhao Chen 001 (CoRR, 2025)

MetaScale: Test-Time Scaling with Evolving Meta-Thoughts. - Qin Liu 010; Wenxuan Zhou; Nan Xu; James Y. Huang; Fei Wang 060; Sheng Zhang 012; Hoifung Poon; Muhao Chen 001 (CoRR, 2025)

X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains. - Qianchu Liu; Sheng Zhang 012; Guanghui Qin; Timothy Ossowski; Yu Gu 017; Ying Jin; Sid Kiblawi; Sam Preston; Mu Wei; Paul Vozila; Tristan Naumann; Hoifung Poon (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)