Analysis of Nonstationary Time Series Using Support Vector Machines. - Ming-Wei Chang; Chih-Jen Lin; Ruby C. Weng (SVM, 2002)

Analysis of switching dynamics with competing support vector machines. - Ming-Wei Chang; Chih-Jen Lin; Ruby Chiu-Hsing Weng (IEEE Trans. Neural Networks, 2004)

Leave-One-Out Bounds for Support Vector Regression Model Selection. - Ming-Wei Chang; Chih-Jen Lin (Neural Comput., 2005)

A Pipeline Framework for Dependency Parsing. - Ming-Wei Chang; Quang Do; Dan Roth 001 (ACL, 2006)

A Pipeline Model for Bottom-Up Dependency Parsing. - Ming-Wei Chang; Quang Do; Dan Roth 001 (CoNLL, 2006)

Guiding Semi-Supervision with Constraint-Driven Learning. - Ming-Wei Chang; Lev-Arie Ratinov; Dan Roth 001 (ACL, 2007)

Simulation and fabrication of HF microelectromechanical bandpass filter. - Ching-Liang Dai; Ming-Chao Chiang; Ming-Wei Chang (Microelectron. J., 2007)

Modeling and fabrication of a microelectromechanical microwave switch. - Ching-Liang Dai; Heng-Ming Hsu; Ming-Chang Tsai; Ming-Ming Hsieh; Ming-Wei Chang (Microelectron. J., 2007)

Fabrication and characterization of a microelectromechanical tunable capacitor. - Ching-Liang Dai; Shih-Chieh Lin; Ming-Wei Chang (Microelectron. J., 2007)

Learning and Inference with Constraints. - Ming-Wei Chang; Lev-Arie Ratinov; Nicholas Rizzolo; Dan Roth 001 (AAAI, 2008)

Importance of Semantic Representation: Dataless Classification. - Ming-Wei Chang; Lev-Arie Ratinov; Dan Roth 001; Vivek Srikumar (AAAI, 2008)

Personalized Spam Filtering for Gray Mail. - Ming-Wei Chang; Scott Yih; Robert McCann (CEAS, 2008)

Partitioned logistic regression for spam filtering. - Ming-Wei Chang; Wen-tau Yih; Christopher Meek (KDD, 2008)

Energy-Efficient Real-Time Co-scheduling of Multimedia DSP Jobs. - Chien-Wei Chen; Chuan-Yue Yang; Tei-Wei Kuo; Ming-Wei Chang (SUTC, 2008)

Implementation and Optimization of DSP Suspend Resume on Dual-Core SOC. - Ming-Wei Chang; Shau-Yin Tseng; Homn Lin; Ching-Lung Su (ICESS, 2009)

Unsupervised Constraint Driven Learning For Transliteration Discovery. - Ming-Wei Chang; Dan Goldwasser; Dan Roth 001; Yuancheng Tu (HLT-NAACL, 2009)

Relation Alignment for Textual Entailment Recognition. - Mark Sammons; V. G. Vinod Vydiswaran; Tim Vieira; Nikhil Johri; Ming-Wei Chang; Dan Goldwasser; Vivek Srikumar; Gourab Kundu; Yuancheng Tu; Kevin Small; Joshua S. Rule; Quang Do; et al. (TAC, 2009)

Driving Semantic Parsing from the World's Response. - James Clarke; Dan Goldwasser; Ming-Wei Chang; Dan Roth 001 (CoNLL, 2010)

The Necessity of Combining Adaptation Methods. - Ming-Wei Chang; Michael Connor; Dan Roth 001 (EMNLP, 2010)

Structured Output Learning with Indirect Supervision. - Ming-Wei Chang; Vivek Srikumar; Dan Goldwasser; Dan Roth 001 (ICML, 2010)

Discriminative Learning over Constrained Latent Representations. - Ming-Wei Chang; Dan Goldwasser; Dan Roth 001; Vivek Srikumar (HLT-NAACL, 2010)

Novel Approach to Fuzzy-Wavelet ECG Signal Analysis for a Mobile Device. - Ching-En Tseng; Ching-Yu Peng; Ming-Wei Chang; Jia-Yush Yen; Chih-Kung Lee; Tse-Shih Huang (J. Medical Syst., 2010)

Modified Frequency-Partitioned Spectrum Estimation for a Wireless Health Advanced Monitoring Bio-Diagnosis System. - Ching-En Tseng; Jia-Yush Yen; Ming-Wei Chang; Wei-Chien Chang; Chih-Kung Lee (IEEE Trans. Syst. Man Cybern. Part A, 2010)

Structured prediction with indirect supervision. - Ming-Wei Chang; James Clarke; Dan Goldwasser; Lev-Arie Ratinov; Vivek Srikumar; Dan Roth 001 (MLSLP, 2011)

Structured prediction with indirect supervision - Ming-Wei Chang (2011)

Learning shared body plans. - Ian Endres; Vivek Srikumar; Ming-Wei Chang; Derek Hoiem (CVPR, 2012)

Unified Expectation Maximization. - Rajhans Samdani; Ming-Wei Chang; Dan Roth 001 (HLT-NAACL, 2012)

Structured learning with constrained conditional models. - Ming-Wei Chang; Lev-Arie Ratinov; Dan Roth 001 (Mach. Learn., 2012)

Question Answering Using Enhanced Lexical Semantic Models. - Wen-tau Yih; Ming-Wei Chang; Christopher Meek; Andrzej Pastusiak (ACL (1), 2013)

To Link or Not to Link? A Study on End-to-End Tweet Entity Linking. - Stephen D. Guo; Ming-Wei Chang; Emre Kiciman (HLT-NAACL, 2013)

Personalized ranking model adaptation for web search. - Hongning Wang; Xiaodong He 001; Ming-Wei Chang; Yang Song 008; Ryen W. White; Wei Chu (SIGIR, 2013)

Learning to extract cross-session search tasks. - Hongning Wang; Yang Song 008; Ming-Wei Chang; Xiaodong He 001; Ryen W. White; Wei Chu (WWW, 2013)

Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction. - Ming-Wei Chang; Wen-tau Yih (Trans. Assoc. Comput. Linguistics, 2013)

Wikification and Beyond: The Challenges of Entity and Concept Grounding. - Dan Roth 001; Heng Ji 001; Ming-Wei Chang; Taylor Cassidy (ACL (Tutorial Abstracts), 2014)

Virtual keyboard for head mounted display-based wearable devices. - Ming-Wei Chang; Tzi-cker Chiueh; Chia-Ming Chang (ICPADS, 2014)

E2E: An End-to-End Entity Linking System for Short and Noisy Text. - Ming-Wei Chang; Bo-June Paul Hsu; Hao Ma 001; Ricky Loynd; Kuansan Wang (#MSM, 2014)

Segmentation based stereo matching using color grouping. - Hsin-Wei Wang; Ming-Wei Chang; Hong Shiang Lin; Ming Ouhyoung (SIGGRAPH Posters, 2014)

Modeling action-level satisfaction for search task satisfaction prediction. - Hongning Wang; Yang Song 008; Ming-Wei Chang; Xiaodong He 001; Ahmed Hassan Awadallah; Ryen W. White (SIGIR, 2014)

ERD'14: Entity Recognition and Disambiguation Challenge. - David Carmel; Ming-Wei Chang; Evgeniy Gabrilovich; Bo-June Paul Hsu; Kuansan Wang (SIGIR Forum, 2014)

Entity Linking on Microblogs with Spatial and Temporal Signals. - Yuan Fang; Ming-Wei Chang (Trans. Assoc. Comput. Linguistics, 2014)

S-MART: Novel Tree-based Structured Learning Algorithms Applied to Tweet Entity Linking. - Yi Yang 038; Ming-Wei Chang (ACL (1), 2015)

Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base. - Wen-tau Yih; Ming-Wei Chang; Xiaodong He 001; Jianfeng Gao 001 (ACL (1), 2015)

Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods. - Arvind Neelakantan; Ming-Wei Chang (HLT-NAACL, 2015)

Placer++: Semantic place labels beyond the visit. - John Krumm; Dany Rouhana; Ming-Wei Chang (PerCom, 2015)

Open Domain Question Answering via Semantic Enrichment. - Huan Sun 001; Hao Ma 001; Wen-tau Yih; Chen-Tse Tsai; Jingjing Liu 001; Ming-Wei Chang (WWW, 2015)

IllinoisSL: A JAVA Library for Structured Prediction. - Kai-Wei Chang; Shyam Upadhyay; Ming-Wei Chang; Vivek Srikumar; Dan Roth 001 (CoRR, 2015)

The Value of Semantic Parse Labeling for Knowledge Base Question Answering. - Wen-tau Yih; Matthew Richardson; Christopher Meek; Ming-Wei Chang; Jina Suh (ACL (2), 2016)

From Entity Linking to Question Answering - Recent Progress on Semantic Grounding Tasks. - Ming-Wei Chang (NUT@COLING, 2016)

Learning from Explicit and Implicit Supervision Jointly For Algebra Word Problems. - Shyam Upadhyay; Ming-Wei Chang; Kai-Wei Chang; Wen-tau Yih (EMNLP, 2016)

Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities. - Yi Yang 038; Ming-Wei Chang; Jacob Eisenstein (EMNLP, 2016)

Answering Complicated Question Intents Expressed in Decomposed Question Sequences. - Mohit Iyyer; Wen-tau Yih; Ming-Wei Chang (CoRR, 2016)

Implicit ReasoNet: Modeling Large-Scale Structured Relationships with Shared Memory. - Yelong Shen; Po-Sen Huang; Ming-Wei Chang; Jianfeng Gao 001 (CoRR, 2016)

Search-based Neural Structured Learning for Sequential Question Answering. - Mohit Iyyer; Wen-tau Yih; Ming-Wei Chang (ACL (1), 2017)

Annotating Derivations: A New Evaluation Strategy and Dataset for Algebra Word Problems. - Shyam Upadhyay; Ming-Wei Chang (EACL (1), 2017)

Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision. - Haoruo Peng; Ming-Wei Chang; Wen-tau Yih (EMNLP, 2017)

Modeling Large-Scale Structured Relationships with Shared Memory for Knowledge Base Completion. - Yelong Shen; Po-Sen Huang; Ming-Wei Chang; Jianfeng Gao 001 (Rep4NLP@ACL, 2017)

A Knowledge-Grounded Neural Conversation Model. - Marjan Ghazvininejad; Chris Brockett; Ming-Wei Chang; Bill Dolan; Jianfeng Gao 001; Wen-tau Yih; Michel Galley (AAAI, 2018)

Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. - Dipendra Misra; Ming-Wei Chang; Xiaodong He 001; Wen-tau Yih (EMNLP, 2018)

Improving Span-based Question Answering Systems with Coarsely Labeled Data. - Hao Cheng 002; Ming-Wei Chang; Kenton Lee; Ankur P. Parikh; Michael Collins 001; Kristina Toutanova (CoRR, 2018)

Handling Divergent Reference Texts when Evaluating Table-to-Text Generation. - Bhuwan Dhingra; Manaal Faruqui; Ankur P. Parikh; Ming-Wei Chang; Dipanjan Das 001; William W. Cohen (ACL (1), 2019)

Latent Retrieval for Weakly Supervised Open Domain Question Answering. - Kenton Lee; Ming-Wei Chang; Kristina Toutanova (ACL (1), 2019)

Zero-Shot Entity Linking by Reading Entity Descriptions. - Lajanugen Logeswaran; Ming-Wei Chang; Kenton Lee; Kristina Toutanova; Jacob Devlin; Honglak Lee (ACL (1), 2019)

BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions. - Christopher Clark; Kenton Lee; Ming-Wei Chang; Tom Kwiatkowski; Michael Collins 001; Kristina Toutanova (NAACL-HLT (1), 2019)

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. - Jacob Devlin; Ming-Wei Chang; Kenton Lee; Kristina Toutanova (NAACL-HLT (1), 2019)

Language Model Pre-training for Hierarchical Document Representations. - Ming-Wei Chang; Kristina Toutanova; Kenton Lee; Jacob Devlin (CoRR, 2019)

Well-Read Students Learn Better: The Impact of Student Initialization on Knowledge Distillation. - Iulia Turc; Ming-Wei Chang; Kenton Lee; Kristina Toutanova (CoRR, 2019)

Natural Questions: a Benchmark for Question Answering Research. - Tom Kwiatkowski; Jennimaria Palomaki; Olivia Redfield; Michael Collins 001; Ankur P. Parikh; Chris Alberti; Danielle Epstein; Illia Polosukhin; Jacob Devlin; Kenton Lee; Kristina Toutanova; Llion Jones; et al. (Trans. Assoc. Comput. Linguistics, 2019)

Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering. - Hao Cheng 002; Ming-Wei Chang; Kenton Lee; Kristina Toutanova (ACL, 2020)

Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing. - Alane Suhr; Ming-Wei Chang; Peter Shaw 004; Kenton Lee (ACL, 2020)

CapWAP: Image Captioning with a Purpose. - Adam Fisch; Kenton Lee; Ming-Wei Chang; Jonathan H. Clark; Regina Barzilay (EMNLP (1), 2020)

Retrieval Augmented Language Model Pre-Training. - Kelvin Guu; Kenton Lee; Zora Tung; Panupong Pasupat; Ming-Wei Chang (ICML, 2020)

REALM: Retrieval-Augmented Language Model Pre-Training. - Kelvin Guu; Kenton Lee; Zora Tung; Panupong Pasupat; Ming-Wei Chang (CoRR, 2020)

CapWAP: Captioning with a Purpose. - Adam Fisch; Kenton Lee; Ming-Wei Chang; Jonathan H. Clark; Regina Barzilay (CoRR, 2020)

Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both? - Peter Shaw 004; Ming-Wei Chang; Panupong Pasupat; Kristina Toutanova (ACL/IJCNLP (1), 2021)

Joint Passage Ranking for Diverse Multi-Answer Retrieval. - Sewon Min; Kenton Lee; Ming-Wei Chang; Kristina Toutanova; Hannaneh Hajishirzi (EMNLP (1), 2021)

Open Question Answering over Tables and Text. - Wenhu Chen; Ming-Wei Chang; Eva Schlinger; William Yang Wang; William W. Cohen (ICLR, 2021)

Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations. - Jonathan Herzig; Peter Shaw 004; Ming-Wei Chang; Kelvin Guu; Panupong Pasupat; Yuan Zhang 001 (CoRR, 2021)

Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer. - Iulia Turc; Kenton Lee; Jacob Eisenstein; Ming-Wei Chang; Kristina Toutanova (CoRR, 2021)

Meta-Learning Fast Weight Language Models. - Kevin Clark; Kelvin Guu; Ming-Wei Chang; Panupong Pasupat; Geoffrey E. Hinton; Mohammad Norouzi 002 (EMNLP, 2022)

Large Dual Encoders Are Generalizable Retrievers. - Jianmo Ni; Chen Qu 001; Jing Lu; Zhuyun Dai; Gustavo Hernández Ábrego; Ji Ma 004; Vincent Y. Zhao; Yi Luan; Keith B. Hall; Ming-Wei Chang; Yinfei Yang (EMNLP, 2022)

ASQA: Factoid Questions Meet Long-Form Answers. - Ivan Stelmakh; Yi Luan; Bhuwan Dhingra; Ming-Wei Chang (EMNLP, 2022)

FRUIT: Faithfully Reflecting Updated Information in Text. - Robert L. Logan IV; Alexandre Passos; Sameer Singh 001; Ming-Wei Chang (NAACL-HLT, 2022)

QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations. - Chaitanya Malaviya; Peter Shaw 004; Ming-Wei Chang; Kenton Lee; Kristina Toutanova (ACL (1), 2023)

Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions? - Yang Chen; Hexiang Hu; Yi Luan; Haitian Sun; Soravit Changpinyo; Alan Ritter; Ming-Wei Chang (EMNLP, 2023)

Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities. - Hexiang Hu; Yi Luan; Yang Chen; Urvashi Khandelwal; Mandar Joshi; Kenton Lee; Kristina Toutanova; Ming-Wei Chang (ICCV, 2023)

Promptagator: Few-shot Dense Retrieval From 8 Examples. - Zhuyun Dai; Vincent Y. Zhao; Ji Ma 004; Yi Luan; Jianmo Ni; Jing Lu; Anton Bakalov; Kelvin Guu; Keith B. Hall; Ming-Wei Chang (ICLR, 2023)

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding. - Kenton Lee; Mandar Joshi; Iulia Raluca Turc; Hexiang Hu; Fangyu Liu 001; Julian Martin Eisenschlos; Urvashi Khandelwal; Peter Shaw 004; Ming-Wei Chang; Kristina Toutanova (ICML, 2023)

Subject-driven Text-to-Image Generation via Apprenticeship Learning. - Wenhu Chen; Hexiang Hu; Yandong Li; Nataniel Ruiz; Xuhui Jia; Ming-Wei Chang; William W. Cohen (NeurIPS, 2023)

Rethinking the Role of Token Retrieval in Multi-Vector Retrieval. - Jinhyuk Lee; Zhuyun Dai; Sai Meher Karthik Duddu; Tao Lei; Iftekhar Naim; Ming-Wei Chang; Vincent Zhao (NeurIPS, 2023)

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. - Tao Lei; Junwen Bai; Siddhartha Brahma; Joshua Ainslie; Kenton Lee; Yanqi Zhou; Nan Du 002; Vincent Y. Zhao; Yuexin Wu; Bo Li 028; Yu Zhang 033; Ming-Wei Chang (NeurIPS, 2023)

Rethinking the Role of Token Retrieval in Multi-Vector Retrieval. - Jinhyuk Lee; Zhuyun Dai; Sai Meher Karthik Duddu; Tao Lei; Iftekhar Naim; Ming-Wei Chang; Vincent Y. Zhao (CoRR, 2023)

Instruct-Imagen: Image Generation with Multi-modal Instruction. - Hexiang Hu; Kelvin C. K. Chan; Yu-Chuan Su; Wenhu Chen; Yandong Li; Kihyuk Sohn; Yang Zhao; Xue Ben; Boqing Gong; William W. Cohen; Ming-Wei Chang; Xuhui Jia (CVPR, 2024)

MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions. - Kai Zhang 033; Yi Luan; Hexiang Hu; Kenton Lee; Siyuan Qiao; Wenhu Chen; Yu Su 001; Ming-Wei Chang (ICML, 2024)

Gecko: Versatile Text Embeddings Distilled from Large Language Models. - Jinhyuk Lee; Zhuyun Dai; Xiaoqi Ren; Blair Chen; Daniel Cer; Jeremy R. Cole; Kai Hui 001; Michael Boratko; Rajvi Kapadia; Wen Ding; Yi Luan; Sai Meher Karthik Duddu; et al. (CoRR, 2024)

Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (CoRR, 2024)

Imagen 3. - Jason Baldridge; Jakob Bauer; Mukul Bhutani; Nicole Brichtova; Andrew Bunner; Kelvin Chan; Yichang Chen; Sander Dieleman; Yuqing Du; Zach Eaton-Rosen; Hongliang Fei; Nando de Freitas; et al. (CoRR, 2024)

KITTEN: A Knowledge-Intensive Evaluation of Image Generation on Visual Entities. - Hsin-Ping Huang; Xinyi Wang; Yonatan Bitton; Hagai Taitelbaum; Gaurav Singh Tomar; Ming-Wei Chang; Xuhui Jia; Kelvin C. K. Chan; Hexiang Hu; Yu-Chuan Su; Ming-Hsuan Yang 001 (CoRR, 2024)

LOFT: Scalable and More Realistic Long-Context Evaluation. - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (NAACL (Findings), 2025)