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Hoifung Poon
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2020 – today
- 2024
- [c52]Yiqing Xie, Sheng Zhang, Hao Cheng, Pengfei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, Carolyn P. Rosé:
DocLens: Multi-aspect Fine-grained Medical Text Evaluation. ACL (1) 2024: 649-679 - [c51]Theodore Zhao, Mu Wei, Joseph Preston, Hoifung Poon:
Pareto Optimal Learning for Estimating Large Language Model Errors. ACL (1) 2024: 10513-10529 - [c50]Alicia Curth, Hoifung Poon, Aditya V. Nori, Javier González:
Cautionary Tales on Synthetic Controls in Survival Analyses. CLeaR 2024: 143-159 - [c49]Fei Wang, Wenxuan Zhou, James Y. Huang, Nan Xu, Sheng Zhang, Hoifung Poon, Muhao Chen:
mDPO: Conditional Preference Optimization for Multimodal Large Language Models. EMNLP 2024: 8078-8088 - [c48]Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon:
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition. ICLR 2024 - [i53]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:
Foundation Models for Biomedical Image Segmentation: A Survey. CoRR abs/2401.07654 (2024) - [i52]Yifeng Liu, Hanwen Xu, Tangqi Fang, Haocheng Xi, Zixuan Liu, Sheng Zhang, Hoifung Poon, Sheng Wang:
T-Rex: Text-assisted Retrosynthesis Prediction. CoRR abs/2401.14637 (2024) - [i51]Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries. CoRR abs/2403.01002 (2024) - [i50]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:
Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging. CoRR abs/2403.08002 (2024) - [i49]James Y. Huang, Wenxuan Zhou, Fei Wang, Fred Morstatter, Sheng Zhang, Hoifung Poon, Muhao Chen:
Offset Unlearning for Large Language Models. CoRR abs/2404.11045 (2024) - [i48]Theodore Zhao, Yu Gu, Jianwei Yang, Naoto Usuyama, Ho Hin Lee, Tristan Naumann, Jianfeng Gao, Angela Crabtree, Jacob Abel, Christine Moung, Brian Piening, Carlo Bifulco, Mu Wei, Hoifung Poon, Sheng Wang:
BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once. CoRR abs/2405.12971 (2024) - [i47]Fei Wang, Xingyu Fu, James Y. Huang, Zekun Li, Qin Liu, Xiaogeng Liu, Mingyu Derek Ma, Nan Xu, Wenxuan Zhou, Kai Zhang, Tianyi Lorena Yan, Wenjie Jacky Mo, Hsiang-Hui Liu, Pan Lu, Chunyuan Li, Chaowei Xiao, Kai-Wei Chang, Dan Roth, Sheng Zhang, Hoifung Poon, Muhao Chen:
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding. CoRR abs/2406.09411 (2024) - [i46]Fei Wang, Wenxuan Zhou, James Y. Huang, Nan Xu, Sheng Zhang, Hoifung Poon, Muhao Chen:
mDPO: Conditional Preference Optimization for Multimodal Large Language Models. CoRR abs/2406.11839 (2024) - [i45]Nan Xu, Fei Wang, Sheng Zhang, Hoifung Poon, Muhao Chen:
From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning. CoRR abs/2407.00902 (2024) - [i44]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 Hyland, Shruthi Bannur, Javier Alvarez-Valle, Xue Li, John Garrett, Alan McMillan, Gaurav Rajguru, Madhu Maddi, Nilesh Vijayrania, Rehaan Bhimai, Nick Mecklenburg, Rupal Jain, Daniel Holstein, Naveen Gaur, Vijay Aski, Jenq-Neng Hwang, Thomas Lin, Ivan Tarapov, Matthew P. Lungren, Mu Wei:
MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging. CoRR abs/2410.06542 (2024) - [i43]Zifeng Wang, Hanyin Wang, Benjamin P. Danek, Ying Li, Christina Mack, Hoifung Poon, Yajuan Wang, Pranav Rajpurkar, Jimeng Sun:
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges. CoRR abs/2411.00024 (2024) - 2023
- [j12]Sam Preston, Mu Wei, Rajesh Rao, Robert Tinn, Naoto Usuyama, Michael Lucas, Yu Gu, Roshanthi Weerasinghe, Soohee Lee, Brian Piening, Paul Tittel, Naveen Valluri, Tristan Naumann, Carlo Bifulco, Hoifung Poon:
Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. Patterns 4(4): 100726 (2023) - [j11]Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann
, Jianfeng Gao, Hoifung Poon
Fine-tuning large neural language models for biomedical natural language processing. Patterns 4(4): 100729 (2023) - [j10]Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland:
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. Trans. Assoc. Comput. Linguistics 11: 1097-1113 (2023) - [c47]Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon:
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. ACL (1) 2023: 13249-13263 - [c46]Louis Blankemeier, Theodore Zhao, Robert Tinn, Sid Kiblawi, Yu Gu, Akshay Chaudhari, Hoifung Poon, Sheng Zhang, Mu Wei, Joseph Preston:
Interactive Span Recommendation for Biomedical Text. ClinicalNLP@ACL 2023: 373-384 - [c45]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Wetscherek, Robert Tinn, Harshita Sharma
Exploring the Boundaries of GPT-4 in Radiology. EMNLP 2023: 14414-14445 - [c44]Wenxuan Zhou, Sheng Zhang, Hoifung Poon, Muhao Chen:
Context-faithful Prompting for Large Language Models. EMNLP (Findings) 2023: 14544-14556 - [c43]Sheng Zhang, Hao Cheng, Jianfeng Gao, Hoifung Poon:
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning. ICLR 2023 - [c42]Hoifung Poon
Precision Health in the Age of Large Language Models. KDD 2023: 5825-5826 - [c41]Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon:
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. MLHC 2023: 846-862 - [c40]Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao:
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. NeurIPS 2023 - [i42]Cai Yang, Addie Woicik, Hoifung Poon, Sheng Wang:
BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction. CoRR abs/2302.06860 (2023) - [i41]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:
Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing. CoRR abs/2303.00915 (2023) - [i40]Wenxuan Zhou, Sheng Zhang, Hoifung Poon, Muhao Chen:
Context-faithful Prompting for Large Language Models. CoRR abs/2303.11315 (2023) - [i39]Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland:
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. CoRR abs/2303.13386 (2023) - [i38]Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon:
Self-Verification Improves Few-Shot Clinical Information Extraction. CoRR abs/2306.00024 (2023) - [i37]Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao:
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. CoRR abs/2306.00890 (2023) - [i36]Theodore Zhao, Mu Wei, J. Samuel Preston, Hoifung Poon:
Automatic Calibration and Error Correction for Large Language Models via Pareto Optimal Self-Supervision. CoRR abs/2306.16564 (2023) - [i35]Yu Gu, Sheng Zhang, Naoto Usuyama, Yonas Woldesenbet, Cliff Wong, Praneeth Sanapathi, Mu Wei, Naveen Valluri, Erika Strandberg, Tristan Naumann, Hoifung Poon:
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events. CoRR abs/2307.06439 (2023) - [i34]Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon:
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. CoRR abs/2308.02180 (2023) - [i33]Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon:
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition. CoRR abs/2308.03279 (2023) - [i32]Yu Gu, Jianwei Yang, Naoto Usuyama, Chunyuan Li, Sheng Zhang, Matthew P. Lungren, Jianfeng Gao, Hoifung Poon:
BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys. CoRR abs/2310.10765 (2023) - [i31]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma
Exploring the Boundaries of GPT-4 in Radiology. CoRR abs/2310.14573 (2023) - [i30]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:
TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models. CoRR abs/2311.01301 (2023) - [i29]Yiqing Xie, Sheng Zhang, Hao Cheng, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon:
Enhancing Medical Text Evaluation with GPT-4. CoRR abs/2311.09581 (2023) - [i28]Harsha Nori, Yin Tat Lee, Sheng Zhang, Dean Carignan, Richard Edgar, Nicolò Fusi, Nicholas King, Jonathan Larson, Yuanzhi Li, Weishung Liu, Renqian Luo, Scott Mayer McKinney, Robert Osazuwa Ness, Hoifung Poon, Tao Qin, Naoto Usuyama, Christopher M. White, Eric Horvitz:
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. CoRR abs/2311.16452 (2023) - [i27]Wenhui Wang, Shuming Ma, Hanwen Xu, Naoto Usuyama, Jiayu Ding, Hoifung Poon, Furu Wei:
When an Image is Worth 1, 024 x 1, 024 Words: A Case Study in Computational Pathology. CoRR abs/2312.03558 (2023) - 2022
- [j9]Renqian Luo
BioGPT: generative pre-trained transformer for biomedical text generation and mining. Briefings Bioinform. 23(6) (2022) - [j8]Yu Gu
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. ACM Trans. Comput. Heal. 3(1): 2:1-2:23 (2022) - [c39]Benedikt Boecking
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) 2022: 1-21 - [c38]Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Knowledge-Rich Self-Supervision for Biomedical Entity Linking. EMNLP (Findings) 2022: 868-880 - [i26]Sam Preston, Mu Wei, Rajesh Rao, Robert Tinn, Naoto Usuyama, Michael Lucas, Roshanthi Weerasinghe, Soohee Lee, Brian Piening, Paul Tittel, Naveen Valluri, Tristan Naumann, Carlo Bifulco, Hoifung Poon:
Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision. CoRR abs/2203.10442 (2022) - [i25]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:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR abs/2204.09817 (2022) - [i24]Sheng Zhang, Hao Cheng, Jianfeng Gao, Hoifung Poon:
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning. CoRR abs/2208.14565 (2022) - [i23]Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu:
BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining. CoRR abs/2210.10341 (2022) - [i22]Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon:
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. CoRR abs/2212.10823 (2022) - 2021
- [c37]Hunter Lang, Hoifung Poon:
Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic. AAAI 2021: 4978-4986 - [c36]Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon:
Modular Self-Supervision for Document-Level Relation Extraction. EMNLP (1) 2021: 5291-5302 - [c35]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:
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. KDD 2021: 3717-3725 - [c34]Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi:
Targeted Adversarial Training for Natural Language Understanding. NAACL-HLT 2021: 5385-5393 - [p4]Tarek R. Besold, Artur S. d'Avila Garcez, Sebastian Bader
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. Neuro-Symbolic Artificial Intelligence 2021: 1-51 - [p3]Hoifung Poon, Hai Wang, Hunter Lang:
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. Neuro-Symbolic Artificial Intelligence 2021: 311-336 - [i21]Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi:
Targeted Adversarial Training for Natural Language Understanding. CoRR abs/2104.05847 (2021) - [i20]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:
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. CoRR abs/2106.13375 (2021) - [i19]Hoifung Poon, Hai Wang, Hunter Lang:
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. CoRR abs/2107.12591 (2021) - [i18]Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon:
Modular Self-Supervision for Document-Level Relation Extraction. CoRR abs/2109.05362 (2021) - [i17]Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing. CoRR abs/2112.07869 (2021) - [i16]Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Knowledge-Rich Self-Supervised Entity Linking. CoRR abs/2112.07887 (2021) - 2020
- [c33]Xiaodong Liu
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding. ACL (demo) 2020: 118-126 - [i15]Xiaodong Liu, Yu Wang, Jianshu Ji, Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao:
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding. CoRR abs/2002.07972 (2020) - [i14]Xiaodong Liu, Hao Cheng, Pengcheng He, Weizhu Chen, Yu Wang, Hoifung Poon, Jianfeng Gao:
Adversarial Training for Large Neural Language Models. CoRR abs/2004.08994 (2020) - [i13]Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. CoRR abs/2007.15779 (2020) - [i12]Chenyan Xiong, Zhenghao Liu, Si Sun, Zhuyun Dai, Kaitao Zhang, Shi Yu, Zhiyuan Liu, Hoifung Poon, Jianfeng Gao, Paul Bennett:
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search. CoRR abs/2011.01580 (2020) - [i11]Hunter Lang, Hoifung Poon:
Self-supervised self-supervision by combining deep learning and probabilistic logic. CoRR abs/2012.12474 (2020)
2010 – 2019
- 2019
- [j7]Sid Kiblawi
Augmenting subnetwork inference with information extracted from the scientific literature. PLoS Comput. Biol. 15(6) (2019) - [c32]Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon, Jianfeng Gao:
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain. BioNLP@ACL 2019: 399-405 - [c31]Robin Jia, Cliff Wong, Hoifung Poon:
Document-Level N-ary Relation Extraction with Multiscale Representation Learning. NAACL-HLT (1) 2019: 3693-3704 - [i10]Robin Jia, Cliff Wong, Hoifung Poon:
Document-Level N-ary Relation Extraction with Multiscale Representation Learning. CoRR abs/1904.02347 (2019) - [i9]Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon, Jianfeng Gao:
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain. CoRR abs/1906.04382 (2019) - 2018
- [c30]Hai Wang, Hoifung Poon:
Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision. EMNLP 2018: 1891-1902 - [c29]Maxim Grechkin, Hoifung Poon, Bill Howe:
EZLearn: Exploiting Organic Supervision in Automated Data Annotation. IJCAI 2018: 4085-4091 - [i8]Hai Wang, Hoifung Poon:
Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision. CoRR abs/1808.08485 (2018) - 2017
- [j6]Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova, Wen-tau Yih:
Cross-Sentence N-ary Relation Extraction with Graph LSTMs. Trans. Assoc. Comput. Linguistics 5: 101-115 (2017) - [c28]Hoifung Poon, Chris Quirk, Kristina Toutanova, Wen-tau Yih:
NLP for Precision Medicine. ACL (Tutorial Abstracts) 2017: 1-2 - [c27]Chris Quirk, Hoifung Poon:
Distant Supervision for Relation Extraction beyond the Sentence Boundary. EACL (1) 2017: 1171-1182 - [c26]Emmanouil A. Platanios, Hoifung Poon, Tom M. Mitchell, Eric Horvitz:
Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach. NIPS 2017: 4361-4370 - [i7]Emmanouil A. Platanios, Hoifung Poon, Tom M. Mitchell, Eric Horvitz:
Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach. CoRR abs/1705.07086 (2017) - [i6]Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova, Wen-tau Yih:
Cross-Sentence N-ary Relation Extraction with Graph LSTMs. CoRR abs/1708.03743 (2017) - [i5]Maxim Grechkin, Hoifung Poon, Bill Howe:
EZLearn: Exploiting Organic Supervision in Large-Scale Data Annotation. CoRR abs/1709.08600 (2017) - [i4]Tarek R. Besold, Artur S. d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro M. Domingos, Pascal Hitzler, Kai-Uwe Kühnberger, Luís C. Lamb, Daniel Lowd, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, Gerson Zaverucha:
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. CoRR abs/1711.03902 (2017) - 2016
- [c25]Kristina Toutanova, Xi Victoria Lin, Wen-tau Yih, Hoifung Poon, Chris Quirk:
Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text. ACL (1) 2016 - [c24]Pedro M. Domingos, Daniel Lowd, Stanley Kok, Aniruddh Nath, Hoifung Poon, Matthew Richardson, Parag Singla:
Unifying Logical and Statistical AI. LICS 2016: 1-11 - [i3]Chris Quirk, Hoifung Poon:
Distant Supervision for Relation Extraction beyond the Sentence Boundary. CoRR abs/1609.04873 (2016) - 2015
- [c23]Kristina Toutanova, Waleed Ammar, Pallavi Choudhury, Hoifung Poon:
Model Selection for Type-Supervised Learning with Application to POS Tagging. CoNLL 2015: 332-337 - [c22]Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, Michael Gamon:
Representing Text for Joint Embedding of Text and Knowledge Bases. EMNLP 2015: 1499-1509 - [c21]Ankur P. Parikh, Hoifung Poon, Kristina Toutanova:
Grounded Semantic Parsing for Complex Knowledge Extraction. HLT-NAACL 2015: 756-766 - [c20]Hoifung Poon, Kristina Toutanova, Chris Quirk:
Distant Supervision for Cancer Pathway Extraction from Text. Pacific Symposium on Biocomputing 2015: 120-131 - 2014
- [j5]Hoifung Poon, Chris Quirk, Charlie DeZiel, David Heckerman:
Literome: PubMed-scale genomic knowledge base in the cloud. Bioinform. 30(19): 2840-2842 (2014) - 2013
- [c19]Hoifung Poon:
Grounded Unsupervised Semantic Parsing. ACL (1) 2013: 933-943 - [c18]Jackie Chi Kit Cheung, Hoifung Poon, Lucy Vanderwende:
Probabilistic Frame Induction. HLT-NAACL 2013: 837-846 - [i2]Jackie Chi Kit Cheung, Hoifung Poon, Lucy Vanderwende:
Probabilistic Frame Induction. CoRR abs/1302.4813 (2013) - 2012
- [c17]Hoifung Poon:
Unsupervised semantic parsing. MLSLP 2012 - [i1]Hoifung Poon, Pedro M. Domingos:
Sum-Product Networks: A New Deep Architecture. CoRR abs/1202.3732 (2012) - 2011
- [c16]Hoifung Poon, Pedro M. Domingos:
Sum-product networks: A new deep architecture. ICCV Workshops 2011: 689-690 - [c15]Hoifung Poon, Pedro M. Domingos:
Sum-Product Networks: A New Deep Architecture. UAI 2011: 337-346 - 2010
- [c14]Hoifung Poon, Pedro M. Domingos:
Machine Reading: A "Killer App" for Statistical Relational AI. StarAI@AAAI 2010 - [c13]Hoifung Poon, Pedro M. Domingos:
Unsupervised Ontology Induction from Text. ACL 2010: 296-305 - [c12]Hoifung Poon:
Markov Logic in Natural Language Processing: Theory, Algorithms, and Applications. NAACL (Tutorial Abstracts) 2010: 3-4 - [c11]Hoifung Poon, Lucy Vanderwende:
Joint Inference for Knowledge Extraction from Biomedical Literature. HLT-NAACL 2010: 813-821 - [p2]Pedro M. Domingos, Daniel Lowd, Stanley Kok, Aniruddh Nath, Hoifung Poon, Matthew Richardson, Parag Singla:
Markov Logic: A Language and Algorithms for Link Mining. Link Mining 2010: 135-161
2000 – 2009
- 2009
- [c10]Fei Xia, William D. Lewis, Hoifung Poon:
Language ID in the Context of Harvesting Language Data off the Web. EACL 2009: 870-878 - [c9]Hoifung Poon, Pedro M. Domingos:
Unsupervised Semantic Parsing. EMNLP 2009: 1-10 - [c8]Hoifung Poon, Colin Cherry, Kristina Toutanova:
Unsupervised Morphological Segmentation with Log-Linear Models. HLT-NAACL 2009: 209-217 - 2008
- [c7]Hoifung Poon, Pedro M. Domingos, Marc Sumner:
A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC. AAAI 2008: 1075-1080 - [c6]Hoifung Poon, Pedro M. Domingos:
Joint Unsupervised Coreference Resolution with Markov Logic. EMNLP 2008: 650-659 - [c5]Pedro M. Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla:
Just Add Weights: Markov Logic for the Semantic Web. URSW (LNCS Vol.) 2008: 1-25 - [c4]Pedro M. Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla, Marc Sumner, Jue Wang:
Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. SSPR/SPR 2008: 3 - [p1]Pedro M. Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla:
Markov Logic. Probabilistic Inductive Logic Programming 2008: 92-117 - 2007
- [c3]Hoifung Poon, Pedro M. Domingos:
Joint Inference in Information Extraction. AAAI 2007: 913-918 - 2006
- [c2]Pedro M. Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla:
Unifying Logical and Statistical AI. AAAI 2006: 2-9 - [c1]Hoifung Poon, Pedro M. Domingos:
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. AAAI 2006: 458-463 - 2005
- [j4]Hong-Jian Lai, Xiangwen Li, Hoifung Poon, Yongbin Ou:
Spanning Trails Connecting Given Edges. Graphs Comb. 21(1): 77-88 (2005) - [j3]Hong-Jian Lai, Xiangwen Li, Hoifung Poon:
Nowhere zero 4-flow in regular matroids. J. Graph Theory 49(3): 196-204 (2005) - 2003
- [j2]Hong-Jian Lai, Bruce Montgomery, Hoifung Poon:
Upper Bounds of Dynamic Chromatic Number. Ars Comb. 68 (2003) - 2002
- [j1]Hong-Jian Lai, Hoifung Poon:
Cycle Cover Ratio of Regular Matroids. Eur. J. Comb. 23(8): 1007-1014 (2002)
Coauthor Index
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