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ORCIDMark Dredze
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- affiliation: Johns Hopkins University, Baltimore, MD, USA
- affiliation (former): University of Pennsylvania, Philadelphia, PA, USA
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Books and Theses
- 2017
[b1]Michael J. Paul, Mark Dredze:
Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services, Morgan & Claypool Publishers 2017, ISBN 978-3-031-01183-2
Journal Articles
- 2022
- [j17]Anna L. Buczak, Benjamin D. Baugher, Christine S. Martin, Meg W. Keiley-Listermann, James Howard, Nathan H. Parrish, Anton Q. Stalick, Daniel S. Berman, Mark Dredze:
Crystal Cube: Forecasting Disruptive Events. Appl. Artif. Intell. 36(1) (2022) - 2021
- [j16]Aaron Mueller, Zach Wood-Doughty, Silvio Amir, Mark Dredze, Alicia Lynn Nobles:
Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 107:1-107:28 (2021) - 2019
- [j15]Yuchen Zhou, Mark Dredze, David A. Broniatowski, William D. Adler:
Elites and foreign actors among the alt-right: The Gab social media platform. First Monday 24(9) (2019) - [j14]Tao Chen
, Mark Dredze, Jonathan P. Weiner, Hadi Kharrazi:
Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records. J. Am. Medical Informatics Assoc. 26(8-9): 787-795 (2019) - 2018
- [j13]John W. Ayers, Theodore L. Caputi, Camille Nebeker, Mark Dredze:
Don't quote me: reverse identification of research participants in social media studies. npj Digit. Medicine 1 (2018) - 2017
- [j12]Ning Gao, Mark Dredze, Douglas W. Oard:
Person entity linking in email with NIL detection. J. Assoc. Inf. Sci. Technol. 68(10): 2412-2424 (2017) - 2015
- [j11]Mauricio Santillana, André T. Nguyen, Mark Dredze, Michael J. Paul, Elaine O. Nsoesie, John S. Brownstein:
Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance. PLoS Comput. Biol. 11(10) (2015) - [j10]Michael J. Paul, Mark Dredze:
SPRITE: Generalizing Topic Models with Structured Priors. Trans. Assoc. Comput. Linguistics 3: 43-57 (2015) - [j9]Mo Yu, Mark Dredze:
Learning Composition Models for Phrase Embeddings. Trans. Assoc. Comput. Linguistics 3: 227-242 (2015) - [j8]Matthew R. Gormley, Mark Dredze, Jason Eisner:
Approximation-Aware Dependency Parsing by Belief Propagation. Trans. Assoc. Comput. Linguistics 3: 489-501 (2015) - 2014
- [j7]Ahmed Abbasi, Donald A. Adjeroh, Mark Dredze, Michael J. Paul, Fatemeh "Mariam" Zahedi, Huimin Zhao, Nitin Walia, Hemant K. Jain, Patrick Sanvanson, Reza Shaker, Marco D. Huesch, Richard Beal, Wanhong Zheng, Marie Abate, Arun Ross:
Social Media Analytics for Smart Health. IEEE Intell. Syst. 29(2): 60-80 (2014) - [j6]Byron C. Wallace, Michael J. Paul, Urmimala Sarkar, Thomas A. Trikalinos, Mark Dredze:
A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews. J. Am. Medical Informatics Assoc. 21(6): 1098-1103 (2014) - 2013
- [j5]Koby Crammer, Alex Kulesza, Mark Dredze:
Adaptive regularization of weight vectors. Mach. Learn. 91(2): 155-187 (2013) - 2012
- [j4]Mark Dredze:
How Social Media Will Change Public Health. IEEE Intell. Syst. 27(4): 81-84 (2012) - [j3]Koby Crammer, Mark Dredze, Fernando Pereira:
Confidence-Weighted Linear Classification for Text Categorization. J. Mach. Learn. Res. 13: 1891-1926 (2012) - 2010
- [j2]Mark Dredze, Alex Kulesza, Koby Crammer:
Multi-domain learning by confidence-weighted parameter combination. Mach. Learn. 79(1-2): 123-149 (2010) - 2009
- [j1]Razvan C. Bunescu, Vitor R. Carvalho, Jan Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H. Göker, Hans W. Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker, Wolfgang Ketter, Alfred Kobsa, Sven Koenig, Tessa A. Lau, Lundy Lewis, Eric T. Matson, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Joelle Pineau, Pascal Poupart, Anita Raja, Wheeler Ruml, Norman M. Sadeh, Guy Shani, Daniel G. Shapiro, Sarabjot Singh Anand, Matthew E. Taylor, Kiri Wagstaff, Trey Smith, William E. Walsh, Rong Zhou:
AAAI 2008 Workshop Reports. AI Mag. 30(1): 108-118 (2009)
Conference and Workshop Papers
- 2023
- [c144]Keith Harrigian, Ayah Zirikly, Brant Chee, Alya Ahmad, Anne Links, Somnath Saha, Mary Catherine Beach, Mark Dredze:
Characterization of Stigmatizing Language in Medical Records. ACL (2) 2023: 312-329 - [c143]Elizabeth Spaulding, Gary Kazantsev, Mark Dredze:
Joint End-to-end Semantic Proto-role Labeling. ACL (2) 2023: 723-736 - [c142]Jingyu Zhang, Alexandra DeLucia, Chenyu Zhang, Mark Dredze:
Geo-Seq2seq: Twitter User Geolocation on Noisy Data through Sequence to Sequence Learning. ACL (Findings) 2023: 4778-4794 - [c141]Shiyue Zhang, Shijie Wu, Ozan Irsoy, Steven Lu, Mohit Bansal, Mark Dredze, David S. Rosenberg:
MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies. ACL (1) 2023: 9027-9050 - 2022
- [c140]Sheena Panthaplackel, Adrian Benton, Mark Dredze:
Updated Headline Generation: Creating Updated Summaries for Evolving News Stories. ACL (1) 2022: 6438-6461 - [c139]Zach Wood-Doughty, Isabel Cachola, Mark Dredze:
Model Distillation for Faithful Explanations of Medical Code Predictions. BioNLP@ACL 2022: 412-425 - [c138]Xiaolei Huang, Franck Dernoncourt, Mark Dredze:
Enriching Unsupervised User Embedding via Medical Concepts. CHIL 2022: 63-78 - [c137]Jingyu Zhang, Alexandra DeLucia, Mark Dredze:
Changes in Tweet Geolocation over Time: A Study with Carmen 2.0. W-NUT@COLING 2022: 1-14 - [c136]David Mueller, Nicholas Andrews, Mark Dredze:
Do Text-to-Text Multi-Task Learners Suffer from Task Conflict? EMNLP (Findings) 2022: 2843-2858 - [c135]Alexandra DeLucia, Shijie Wu, Aaron Mueller, Carlos Aguirre, Philip Resnik, Mark Dredze:
Bernice: A Multilingual Pre-trained Encoder for Twitter. EMNLP 2022: 6191-6205 - [c134]Shijie Wu, Benjamin Van Durme, Mark Dredze:
Zero-shot Cross-lingual Transfer is Under-specified Optimization. RepL4NLP@ACL 2022: 236-248 - [c133]Keith Harrigian, Mark Dredze:
The Problem of Semantic Shift in Longitudinal Monitoring of Social Media: A Case Study on Mental Health During the COVID-19 Pandemic. WebSci 2022: 208-218 - 2021
- [c132]Elliot Schumacher, James Mayfield, Mark Dredze:
Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking. ACL/IJCNLP (Findings) 2021: 583-595 - [c131]Zach Wood-Doughty, Paiheng Xu, Xiao Liu, Mark Dredze:
Using Noisy Self-Reports to Predict Twitter User Demographics. SocialNLP@NAACL 2021: 123-137 - [c130]Abhinav Chinta, Jingyu Zhang, Alexandra DeLucia, Mark Dredze, Anna L. Buczak:
Study of Manifestation of Civil Unrest on Twitter. W-NUT 2021: 396-409 - [c129]Carlos Aguirre, Keith Harrigian, Mark Dredze:
Gender and Racial Fairness in Depression Research using Social Media. EACL 2021: 2932-2949 - [c128]Mahsa Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Guanghui Qin, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton Murray, Aaron Steven White, Mark Dredze, Benjamin Van Durme:
Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction. EMNLP (1) 2021: 1950-1967 - [c127]Zach Wood-Doughty, Isabel Cachola, Mark Dredze:
Proxy Model Explanations for Time Series RNNs. ICMLA 2021: 698-703 - [c126]Aaron Mueller, Mark Dredze:
Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling. NAACL-HLT 2021: 3054-3068 - 2020
- [c125]David Mueller, Nicholas Andrews, Mark Dredze:
Sources of Transfer in Multilingual Named Entity Recognition. ACL 2020: 8093-8104 - [c124]Elliot Schumacher, Andriy Mulyar, Mark Dredze:
Clinical Concept Linking with Contextualized Neural Representations. ACL 2020: 8585-8592 - [c123]Justin Sech, Alexandra DeLucia, Anna L. Buczak, Mark Dredze:
Civil Unrest on Twitter (CUT): A Dataset of Tweets to Support Research on Civil Unrest. W-NUT@EMNLP 2020: 215-221 - [c122]Alicia L. Nobles, Eric C. Leas, Mark Dredze, Christopher A. Longhurst, Davey Smith, John W. Ayers:
Crowd-Diagnosis: When the Public Turns to Social Media to Obtain Clinical Diagnoses. AMIA 2020 - [c121]Keith Harrigian, Carlos Aguirre, Mark Dredze:
Do Models of Mental Health Based on Social Media Data Generalize? EMNLP (Findings) 2020: 3774-3788 - [c120]Shijie Wu, Mark Dredze:
Do Explicit Alignments Robustly Improve Multilingual Encoders? EMNLP (1) 2020: 4471-4482 - [c119]Alicia L. Nobles, Eric C. Leas, Mark Dredze, John W. Ayers:
Examining Peer-to-Peer and Patient-Provider Interactions on a Social Media Community Facilitating Ask the Doctor Services. ICWSM 2020: 464-475 - [c118]Manya Wadhwa, Silvio Amir, Mark Dredze:
Aligning Public Feedback to Requests for Comments on Regulations.gov. ICWSM 2020: 974-978 - [c117]Shijie Wu, Mark Dredze:
Are All Languages Created Equal in Multilingual BERT? RepL4NLP@ACL 2020: 120-130 - 2019
- [c116]Elliot Schumacher, Mark Dredze:
Discriminative Candidate Generation for Medical Concept Linking. AKBC 2019 - [c115]Shijie Wu, Mark Dredze:
Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT. EMNLP/IJCNLP (1) 2019: 833-844 - [c114]Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent:
Visual Attention Model for Cross-Sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning. FLAIRS 2019: 98-103 - 2018
- [c113]Zach Wood-Doughty, Praateek Mahajan, Mark Dredze:
Johns Hopkins or johnny-hopkins: Classifying Individuals versus Organizations on Twitter. PEOPLES@NAACL-HTL 2018: 56-61 - [c112]Zach Wood-Doughty, Nicholas Andrews, Rebecca Marvin, Mark Dredze:
Predicting Twitter User Demographics from Names Alone. PEOPLES@NAACL-HTL 2018: 105-111 - [c111]Adrian Benton, Mark Dredze:
Using Author Embeddings to Improve Tweet Stance Classification. NUT@EMNLP 2018: 184-194 - [c110]Zach Wood-Doughty, Nicholas Andrews, Mark Dredze:
Convolutions Are All You Need (For Classifying Character Sequences). NUT@EMNLP 2018: 208-213 - [c109]Zach Wood-Doughty, Ilya Shpitser, Mark Dredze:
Challenges of Using Text Classifiers for Causal Inference. EMNLP 2018: 4586-4598 - [c108]Ning Gao, Mark Dredze, Douglas W. Oard:
Enhancing Scientific Collaboration Through Knowledge Base Population and Linking for Meetings. HICSS 2018: 1-10 - [c107]Adrian Benton, Mark Dredze:
Deep Dirichlet Multinomial Regression. NAACL-HLT 2018: 365-374 - [c106]Travis Wolfe, Annabelle Carrell, Mark Dredze, Benjamin Van Durme:
Summarizing Entities using Distantly Supervised Information Extractors. ProfS/KG4IR/Data:Search@SIGIR 2018: 51-58 - 2017
- [c105]Xiaolei Huang, Michael C. Smith, Michael J. Paul, Dmytro Ryzhkov, Sandra Crouse Quinn, David A. Broniatowski, Mark Dredze:
Examining Patterns of Influenza Vaccination in Social Media. AAAI Workshops 2017 - [c104]Travis Wolfe, Mark Dredze, Benjamin Van Durme:
Pocket Knowledge Base Population. ACL (2) 2017: 305-310 - [c103]Nicholas Andrews, Mark Dredze, Benjamin Van Durme, Jason Eisner:
Bayesian Modeling of Lexical Resources for Low-Resource Settings. ACL (1) 2017: 1029-1039 - [c102]Zach Wood-Doughty, Michael Smith, David A. Broniatowski, Mark Dredze:
How Does Twitter User Behavior Vary Across Demographic Groups? NLP+CSS@ACL 2017: 83-89 - [c101]Anietie Andy, Mark Dredze, Mugizi Rwebangira, Chris Callison-Burch:
Constructing an Alias List for Named Entities during an Event. NUT@EMNLP 2017: 40-44 - [c100]Michael C. Smith, Mark Dredze, Sandra Crouse Quinn, David A. Broniatowski:
Monitoring Real-time Spatial Public Health Discussions in the Context of Vaccine Hesitancy. SMM4H@AMIA 2017: 12-18 - [c99]Ning Gao, Gregory Sell, Douglas W. Oard, Mark Dredze:
Leveraging side information for speaker identification with the Enron conversational telephone speech collection. ASRU 2017: 577-583 - [c98]Adrian Benton, Glen Coppersmith, Mark Dredze:
Ethical Research Protocols for Social Media Health Research. EthNLP@EACL 2017: 94-102 - [c97]Benjamin Van Durme, Tom Lippincott, Kevin Duh, Deana Burchfield, Adam Poliak, Cash Costello, Tim Finin, Scott Miller, James Mayfield, Philipp Koehn, Craig Harman, Dawn J. Lawrie, Chandler May, Max Thomas, Annabelle Carrell, Julianne Chaloux, Tongfei Chen, Alex Comerford, Mark Dredze, Benjamin Glass, Shudong Hao, Patrick Martin, Pushpendre Rastogi, Rashmi Sankepally, Travis Wolfe, Ying-Ying Tran, Ted Zhang:
CADET: Computer Assisted Discovery Extraction and Translation. IJCNLP (System Demonstrations) 2017: 5-8 - [c96]Nanyun Peng, Mark Dredze:
Multi-task Domain Adaptation for Sequence Tagging. Rep4NLP@ACL 2017: 91-100 - [c95]Ning Gao, Douglas W. Oard, Mark Dredze:
Support for Interactive Identification of Mentioned Entities in Conversational Speech. SIGIR 2017: 953-956 - 2016
- [c94]Adrian Benton, Michael J. Paul, Braden Hancock, Mark Dredze:
Collective Supervision of Topic Models for Predicting Surveys with Social Media. AAAI 2016: 2892-2898 - [c93]Animesh Koratana, Mark Dredze, Margaret S. Chisolm, Matthew W. Johnson, Michael J. Paul:
Studying Anonymous Health Issues and Substance Use on College Campuses with Yik Yak. AAAI Workshop: WWW and Population Health Intelligence 2016 - [c92]Adrian Benton, Raman Arora, Mark Dredze:
Learning Multiview Embeddings of Twitter Users. ACL (2) 2016 - [c91]Nanyun Peng, Mark Dredze:
Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning. ACL (2) 2016 - [c90]Rebecca Knowles, Josh Carroll, Mark Dredze:
Demographer: Extremely Simple Name Demographics. NLP+CSS@EMNLP 2016: 108-113 - [c89]Mark Dredze, Nicholas Andrews, Jay DeYoung:
Twitter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation. SocialNLP@EMNLP 2016: 20-25 - [c88]Anietie Andy, Satoshi Sekine, Mugizi Rwebangira, Mark Dredze:
Name Variation in Community Question Answering Systems. NUT@COLING 2016: 51-60 - [c87]Ning Gao, Mark Dredze, Douglas W. Oard:
Knowledge Base Population for Organization Mentions in Email. AKBC@NAACL-HLT 2016: 24-28 - [c86]Munmun De Choudhury, Emre Kiciman, Mark Dredze, Glen Coppersmith, Mrinal Kumar:
Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media. CHI 2016: 2098-2110 - [c85]Mark Dredze, Prabhanjan Kambadur, Gary Kazantsev, Gideon Mann, Miles Osborne:
How Twitter is Changing the Nature of Financial News Discovery. DSMM@SIGMOD 2016: 2:1-2:5 - [c84]Travis Wolfe, Mark Dredze, Benjamin Van Durme:
A Study of Imitation Learning Methods for Semantic Role Labeling. SPNLP@EMNLP 2016: 44-53 - [c83]Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley:
Embedding Lexical Features via Low-Rank Tensors. HLT-NAACL 2016: 1019-1029 - [c82]Mark Dredze, Miles Osborne, Prabhanjan Kambadur:
Geolocation for Twitter: Timing Matters. HLT-NAACL 2016: 1064-1069 - 2015
- [c81]Michael J. Paul, Mark Dredze, David A. Broniatowski, Nicholas Generous:
Worldwide Influenza Surveillance through Twitter. AAAI Workshop: WWW and Public Health Intelligence 2015 - [c80]Haoyu Wang, Eduard H. Hovy, Mark Dredze:
The Hurricane Sandy Twitter Corpus. AAAI Workshop: WWW and Public Health Intelligence 2015 - [c79]Nanyun Peng, Mo Yu, Mark Dredze:
An Empirical Study of Chinese Name Matching and Applications. ACL (2) 2015: 377-383 - [c78]Ellie Pavlick, Travis Wolfe, Pushpendre Rastogi, Chris Callison-Burch, Mark Dredze, Benjamin Van Durme:
FrameNet+: Fast Paraphrastic Tripling of FrameNet. ACL (2) 2015: 408-413 - [c77]Nanyun Peng, Mark Dredze:
Named Entity Recognition for Chinese Social Media with Jointly Trained Embeddings. EMNLP 2015: 548-554 - [c76]Matthew R. Gormley, Mo Yu, Mark Dredze:
Improved Relation Extraction with Feature-Rich Compositional Embedding Models. EMNLP 2015: 1774-1784 - [c75]Mrinal Kumar, Mark Dredze, Glen Coppersmith, Munmun De Choudhury:
Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides. HT 2015: 85-94 - [c74]Glen Coppersmith, Mark Dredze, Craig Harman, Kristy Hollingshead:
From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses. CLPsych@HLT-NAACL 2015: 1-10 - [c73]Travis Wolfe, Mark Dredze, Benjamin Van Durme:
Predicate Argument Alignment using a Global Coherence Model. HLT-NAACL 2015: 11-20 - [c72]Glen Coppersmith, Mark Dredze, Craig Harman, Kristy Hollingshead, Margaret Mitchell:
CLPsych 2015 Shared Task: Depression and PTSD on Twitter. CLPsych@HLT-NAACL 2015: 31-39 - [c71]Nanyun Peng, Francis Ferraro, Mo Yu, Nicholas Andrews, Jay DeYoung, Max Thomas, Matthew R. Gormley, Travis Wolfe, Craig Harman, Benjamin Van Durme, Mark Dredze:
A Concrete Chinese NLP Pipeline. HLT-NAACL 2015: 86-90 - [c70]Adrian Benton, Mark Dredze:
Entity Linking for Spoken Language. HLT-NAACL 2015: 225-230 - [c69]Mo Yu, Matthew R. Gormley, Mark Dredze:
Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction. HLT-NAACL 2015: 1374-1379 - 2014
- [c68]Mo Yu, Mark Dredze:
Improving Lexical Embeddings with Semantic Knowledge. ACL (2) 2014: 545-550 - [c67]Nanyun Peng, Yiming Wang, Mark Dredze:
Learning Polylingual Topic Models from Code-Switched Social Media Documents. ACL (2) 2014: 674-679 - [c66]Nicholas Andrews, Jason Eisner, Mark Dredze:
Robust Entity Clustering via Phylogenetic Inference. ACL (1) 2014: 775-785 - [c65]Matthew R. Gormley, Margaret Mitchell, Benjamin Van Durme, Mark Dredze:
Low-Resource Semantic Role Labeling. ACL (1) 2014: 1177-1187 - [c64]Glen Coppersmith, Mark Dredze, Craig Harman:
Quantifying Mental Health Signals in Twitter. CLPsych@ACL 2014: 51-60 - [c63]Glen Coppersmith, Craig Harman, Mark Dredze:
Measuring Post Traumatic Stress Disorder in Twitter. ICWSM 2014 - [c62]Miles Osborne, Mark Dredze:
Facebook, Twitter and Google Plus for Breaking News: Is There a Winner? ICWSM 2014 - 2013
- [c61]Travis Wolfe, Benjamin Van Durme, Mark Dredze, Nicholas Andrews, Charley Beller, Chris Callison-Burch, Jay DeYoung, Justin Snyder, Jonathan Weese, Tan Xu, Xuchen Yao:
PARMA: A Predicate Argument Aligner. ACL (2) 2013: 63-68 - [c60]Justin Snyder, Rebecca Knowles, Mark Dredze, Matthew R. Gormley, Travis Wolfe:
Topic Models and Metadata for Visualizing Text Corpora. HLT-NAACL 2013: 5-9 - [c59]Michael J. Paul, Mark Dredze:
Drug Extraction from the Web: Summarizing Drug Experiences with Multi-Dimensional Topic Models. HLT-NAACL 2013: 168-178 - [c58]Mahesh Joshi, Mark Dredze, William W. Cohen, Carolyn P. Rosé:
What's in a Domain? Multi-Domain Learning for Multi-Attribute Data. HLT-NAACL 2013: 685-690 - [c57]Alex Lamb, Michael J. Paul, Mark Dredze:
Separating Fact from Fear: Tracking Flu Infections on Twitter. HLT-NAACL 2013: 789-795 - [c56]Shane Bergsma, Mark Dredze, Benjamin Van Durme, Theresa Wilson, David Yarowsky:
Broadly Improving User Classification via Communication-Based Name and Location Clustering on Twitter. HLT-NAACL 2013: 1010-1019 - 2012
- [c55]Alex Lamb, Michael J. Paul, Mark Dredze:
Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics. AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text 2012 - [c54]Atul Nakhasi, Ralph Passarella, Sarah G. Bell, Michael J. Paul, Mark Dredze, Peter Pronovost:
Malpractice and Malcontent: Analyzing Medical Complaints in Twitter. AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text 2012 - [c53]Michael J. Paul, Mark Dredze:
Experimenting with Drugs (and Topic Models): Multi-Dimensional Exploration of Recreational Drug Discussions. AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text 2012 - [c52]Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur:
Fast Syntactic Analysis for Statistical Language Modeling via Substructure Sharing and Uptraining. ACL (1) 2012: 175-183 - [c51]Ralph Passarella, Atul Nakhasi, Sarah G. Bell, Michael J. Paul, Peter Pronovost, Mark Dredze:
Twitter as a Source for Learning about Patient Safety Events. AMIA 2012 - [c50]Nicholas Andrews, Jason Eisner, Mark Dredze:
Name Phylogeny: A Generative Model of String Variation. EMNLP-CoNLL 2012: 344-355 - [c49]Mahesh Joshi, Mark Dredze, William W. Cohen, Carolyn P. Rosé:
Multi-Domain Learning: When Do Domains Matter? EMNLP-CoNLL 2012: 1302-1312 - [c48]Koby Crammer, Alex Kulesza, Mark Dredze:
New ℌ∞ bounds for the recursive least squares algorithm exploiting input structure. ICASSP 2012: 2017-2020 - [c47]Damianos G. Karakos, Brian Roark, Izhak Shafran, Kenji Sagae, Maider Lehr, Emily Tucker Prud'hommeaux, Puyang Xu, Nathan Glenn, Sanjeev Khudanpur, Murat Saraclar, Daniel M. Bikel, Mark Dredze, Chris Callison-Burch, Yuan Cao, Keith B. Hall, Eva Hasler, Philipp Koehn, Adam Lopez, Matt Post, Darcey Riley:
Deriving conversation-based features from unlabeled speech for discriminative language modeling. INTERSPEECH 2012: 202-205 - [c46]Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur:
Efficient Structured Language Modeling for Speech Recognition. INTERSPEECH 2012: 1660-1663 - [c45]Ariya Rastrow, Sanjeev Khudanpur, Mark Dredze:
Revisiting the Case for Explicit Syntactic Information in Language Models. WLM@NAACL-HLT 2012: 50-58 - [c44]Spence Green, Nicholas Andrews, Matthew R. Gormley, Mark Dredze, Christopher D. Manning:
Entity Clustering Across Languages. HLT-NAACL 2012: 60-69 - [c43]Matthew R. Gormley, Mark Dredze, Benjamin Van Durme, Jason Eisner:
Shared Components Topic Models. HLT-NAACL 2012: 783-792 - [c42]Michael J. Paul, Mark Dredze:
Factorial LDA: Sparse Multi-Dimensional Text Models. NIPS 2012: 2591-2599 - 2011
- [c41]Carolina Parada, Mark Dredze, Abhinav Sethy, Ariya Rastrow:
Learning Sub-Word Units for Open Vocabulary Speech Recognition. ACL 2011: 712-721 - [c40]Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur:
Efficient discriminative training of long-span language models. ASRU 2011: 214-219 - [c39]Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur:
Adapting n-gram maximum entropy language models with conditional entropy regularization. ASRU 2011: 220-225 - [c38]Damianos G. Karakos, Mark Dredze, Ken Ward Church, Aren Jansen, Sanjeev Khudanpur:
Estimating document frequencies in a speech corpus. ASRU 2011: 407-412 - [c37]Ariya Rastrow, Markus Dreyer, Abhinav Sethy, Sanjeev Khudanpur, Bhuvana Ramabhadran, Mark Dredze:
Hill climbing on speech lattices: A new rescoring framework. ICASSP 2011: 5032-5035 - [c36]Michael J. Paul, Mark Dredze:
You Are What You Tweet: Analyzing Twitter for Public Health. ICWSM 2011 - [c35]Carolina Parada, Mark Dredze, Frederick Jelinek:
OOV Sensitive Named-Entity Recognition in Speech. INTERSPEECH 2011: 2085-2088 - 2010
- [c34]Mark Dredze, Paul McNamee, Delip Rao, Adam Gerber, Tim Finin:
Entity Disambiguation for Knowledge Base Population. COLING 2010: 277-285 - [c33]Delip Rao, Paul McNamee, Mark Dredze:
Streaming Cross Document Entity Coreference Resolution. COLING (Posters) 2010: 1050-1058 - [c32]Mark Dredze, Aren Jansen, Glen Coppersmith, Ken Ward Church:
NLP on Spoken Documents Without ASR. EMNLP 2010: 460-470 - [c31]Mark Dredze, Tim Oates, Christine D. Piatko:
We're Not in Kansas Anymore: Detecting Domain Changes in Streams. EMNLP 2010: 585-595 - [c30]Carolina Parada, Abhinav Sethy, Mark Dredze, Frederick Jelinek:
A spoken term detection framework for recovering out-of-vocabulary words using the web. INTERSPEECH 2010: 1269-1272 - [c29]Chris Callison-Burch, Mark Dredze:
Creating Speech and Language Data With Amazon's Mechanical Turk. Mturk@HLT-NAACL 2010: 1-12 - [c28]Tim Finin, William Murnane, Anand Karandikar, Nicholas Keller, Justin Martineau, Mark Dredze:
Annotating Named Entities in Twitter Data with Crowdsourcing. Mturk@HLT-NAACL 2010: 80-88 - [c27]Matthew R. Gormley, Adam Gerber, Mary P. Harper, Mark Dredze:
Non-Expert Correction of Automatically Generated Relation Annotations. Mturk@HLT-NAACL 2010: 204-207 - [c26]Carolina Parada, Mark Dredze, Denis Filimonov, Frederick Jelinek:
Contextual Information Improves OOV Detection in Speech. HLT-NAACL 2010: 216-224 - [c25]Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul, Fernando Pereira:
Exploiting Feature Covariance in High-Dimensional Online Learning. AISTATS 2010: 493-500 - 2009
- [c24]Koby Crammer, Mark Dredze, Alex Kulesza:
Multi-Class Confidence Weighted Algorithms. EMNLP 2009: 496-504 - [c23]Mark Dredze, Bill N. Schilit, Peter Norvig:
Suggesting Email View Filters for Triage and Search. IJCAI 2009: 1414-1419 - [c22]Koby Crammer, Alex Kulesza, Mark Dredze:
Adaptive Regularization of Weight Vectors. NIPS 2009: 414-422 - 2008
- [c21]Mark Dredze, Hanna M. Wallach, Danny Puller, Tova Brooks, Josh Carroll, Joshua Magarick, John Blitzer, Fernando Pereira:
Intelligent Email: Aiding Users with AI. AAAI 2008: 1524-1527 - [c20]Mark Dredze, Joel Wallenberg:
Icelandic Data Driven Part of Speech Tagging. ACL (2) 2008: 33-36 - [c19]Mark Dredze, Koby Crammer:
Active Learning with Confidence. ACL (2) 2008: 233-236 - [c18]Kevin Lerman, Ari Gilder, Mark Dredze, Fernando Pereira:
Reading the Markets: Forecasting Public Opinion of Political Candidates by News Analysis. COLING 2008: 473-480 - [c17]Mark Dredze, Koby Crammer:
Online Methods for Multi-Domain Learning and Adaptation. EMNLP 2008: 689-697 - [c16]Mark Dredze, Koby Crammer, Fernando Pereira:
Confidence-weighted linear classification. ICML 2008: 264-271 - [c15]Mark Dredze, Hanna M. Wallach, Danny Puller, Fernando Pereira:
Generating summary keywords for emails using topics. IUI 2008: 199-206 - [c14]Mark Dredze, Tova Brooks, Josh Carroll, Joshua Magarick, John Blitzer, Fernando Pereira:
Intelligent email: reply and attachment prediction. IUI 2008: 321-324 - [c13]Koby Crammer, Mark Dredze, Fernando Pereira:
Exact Convex Confidence-Weighted Learning. NIPS 2008: 345-352 - 2007
- [c12]John Blitzer, Mark Dredze, Fernando Pereira:
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification. ACL 2007 - [c11]Koby Crammer, Mark Dredze, Kuzman Ganchev, Partha Pratim Talukdar, Steven Carroll:
Automatic Code Assignment to Medical Text. BioNLP@ACL 2007: 129-136 - [c10]Mark Dredze, Reuven Gevaryahu, Ari Elias-Bachrach:
Learning Fast Classifiers for Image Spam. CEAS 2007 - [c9]Mark Dredze, John Blitzer, Partha Pratim Talukdar, Kuzman Ganchev, João Graça, Fernando C. N. Pereira:
Frustratingly Hard Domain Adaptation for Dependency Parsing. EMNLP-CoNLL 2007: 1051-1055 - 2006
- [c8]Nicholas Kushmerick, Tessa A. Lau, Mark Dredze, Rinat Khoussainov:
Activity-Centric Email: A Machine Learning Approach. AAAI 2006: 1634-1637 - [c7]Mark Dredze, John Blitzer, Fernando Pereira:
"Sorry, I Forgot the Attachment": Email Attachment Prediction. CEAS 2006 - [c6]Mark Dredze, Tessa A. Lau, Nicholas Kushmerick:
Automatically classifying emails into activities. IUI 2006: 70-77 - 2005
- [c5]Mark Dredze, John Blitzer, Fernando Pereira:
Reply Expectation Prediction for Email Management. CEAS 2005 - [c4]Catalina Danis, Wendy A. Kellogg, Tessa A. Lau, Mark Dredze, Jeffrey Stylos, Nicholas Kushmerick:
Managers' email: beyond tasks and to-dos. CHI Extended Abstracts 2005: 1324-1327 - [c3]Rie Kubota Ando, Mark Dredze, Tong Zhang:
TREC 2005 Genomics Track Experiments at IBM Watson. TREC 2005 - 2003
- [c2]Kevin Livingston, Mark Dredze, Kristian J. Hammond, Larry Birnbaum:
Beyond broadcast. IUI 2003: 260-262 - [c1]Kevin Livingston, Mark Dredze, Kristian J. Hammond, Larry Birnbaum:
Beyond broadcast: a demo. IUI 2003: 325
Parts in Books or Collections
- 2013
- [p1]Delip Rao, Paul McNamee, Mark Dredze:
Entity Linking: Finding Extracted Entities in a Knowledge Base. Multi-source, Multilingual Information Extraction and Summarization 2013: 93-115
Editorship
- 2020
- [e3]Karin Verspoor, Kevin Bretonnel Cohen, Michael Conway, Berry de Bruijn, Mark Dredze, Rada Mihalcea, Byron C. Wallace:
Proceedings of the 1st Workshop on NLP for COVID-19@ EMNLP 2020, Online, December 2020. Association for Computational Linguistics 2020 [contents] - 2017
- [e2]Allyson Ettinger, Spandana Gella, Matthieu Labeau, Cecilia Ovesdotter Alm, Marine Carpuat, Mark Dredze:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30 - August 4, Student Research Workshop. Association for Computational Linguistics 2017, ISBN 978-1-945626-56-2 [contents] - 2010
- [e1]Chris Callison-Burch, Mark Dredze:
Proceedings of the 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Los Angeles, USA, June 6, 2010. Association for Computational Linguistics 2010 [contents]
Informal and Other Publications
- 2024
- [i51]Hanjie Chen, Zhouxiang Fang, Yash Singla, Mark Dredze:
Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions. CoRR abs/2402.18060 (2024) - [i50]Sharon Levy, Tahilin Sanchez Karver, William D. Adler, Michelle R. Kaufman, Mark Dredze:
Evaluating Biases in Context-Dependent Health Questions. CoRR abs/2403.04858 (2024) - [i49]Miriam Wanner, Seth Ebner, Zhengping Jiang, Mark Dredze, Benjamin Van Durme:
A Closer Look at Claim Decomposition. CoRR abs/2403.11903 (2024) - 2023
- [i48]Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David S. Rosenberg, Gideon Mann:
BloombergGPT: A Large Language Model for Finance. CoRR abs/2303.17564 (2023) - [i47]Carlos Aguirre, Mark Dredze:
Generalizing Fairness using Multi-Task Learning without Demographic Information. CoRR abs/2305.12671 (2023) - [i46]Shiyue Zhang, Shijie Wu, Ozan Irsoy, Steven Lu, Mohit Bansal, Mark Dredze, David S. Rosenberg:
MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies. CoRR abs/2305.16958 (2023) - [i45]Carlos Aguirre, Kuleen Sasse, Isabel Cachola, Mark Dredze:
Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models. CoRR abs/2311.08472 (2023) - [i44]Keith Harrigian, Tina Tang, Anthony Gonzales, Cindy X. Cai, Mark Dredze:
An Eye on Clinical BERT: Investigating Language Model Generalization for Diabetic Eye Disease Phenotyping. CoRR abs/2311.08687 (2023) - [i43]Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa:
Use large language models to promote equity. CoRR abs/2312.14804 (2023) - 2022
- [i42]Xiaolei Huang, Franck Dernoncourt, Mark Dredze:
Enriching Unsupervised User Embedding via Medical Concepts. CoRR abs/2203.10627 (2022) - [i41]Moniba Keymanesh, Adrian Benton, Mark Dredze:
What Makes Data-to-Text Generation Hard for Pretrained Language Models? CoRR abs/2205.11505 (2022) - [i40]Keith Harrigian, Mark Dredze:
Then and Now: Quantifying the Longitudinal Validity of Self-Disclosed Depression Diagnoses. CoRR abs/2206.11155 (2022) - [i39]Keith Harrigian, Mark Dredze:
The Problem of Semantic Shift in Longitudinal Monitoring of Social Media: A Case Study on Mental Health During the COVID-19 Pandemic. CoRR abs/2206.11160 (2022) - [i38]Shijie Wu, Benjamin Van Durme, Mark Dredze:
Zero-shot Cross-lingual Transfer is Under-specified Optimization. CoRR abs/2207.05666 (2022) - [i37]Carlos Aguirre, Mark Dredze, Philip Resnik:
Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics. CoRR abs/2211.07932 (2022) - [i36]David Mueller, Nicholas Andrews, Mark Dredze:
Do Text-to-Text Multi-Task Learners Suffer from Task Conflict? CoRR abs/2212.06645 (2022) - 2021
- [i35]Zach Wood-Doughty, Ilya Shpitser, Mark Dredze:
Generating Synthetic Text Data to Evaluate Causal Inference Methods. CoRR abs/2102.05638 (2021) - [i34]Xiaolei Huang, Michael J. Paul, Robin Burke, Franck Dernoncourt, Mark Dredze:
User Factor Adaptation for User Embedding via Multitask Learning. CoRR abs/2102.11103 (2021) - [i33]Carlos Aguirre, Keith Harrigian, Mark Dredze:
Gender and Racial Fairness in Depression Research using Social Media. CoRR abs/2103.10550 (2021) - [i32]Aaron Mueller, Mark Dredze:
Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling. CoRR abs/2104.05064 (2021) - [i31]Zach Wood-Doughty, Isabel Cachola, Mark Dredze:
Faithful and Plausible Explanations of Medical Code Predictions. CoRR abs/2104.07894 (2021) - [i30]Elliot Schumacher, James Mayfield, Mark Dredze:
Improving Zero-Shot Multi-Lingual Entity Linking. CoRR abs/2104.08082 (2021) - [i29]Yuval Pinter, Amanda Stent, Mark Dredze, Jacob Eisenstein:
Learning to Look Inside: Augmenting Token-Based Encoders with Character-Level Information. CoRR abs/2108.00391 (2021) - [i28]Mahsa Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Guanghui Qin, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton Murray, Aaron Steven White, Mark Dredze, Benjamin Van Durme:
Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction. CoRR abs/2109.06798 (2021) - 2020
- [i27]Paiheng Xu, Mark Dredze, David A. Broniatowski:
The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets. CoRR abs/2004.02397 (2020) - [i26]Zach Wood-Doughty, Paiheng Xu, Xiao Liu, Mark Dredze:
Using Noisy Self-Reports to Predict Twitter User Demographics. CoRR abs/2005.00635 (2020) - [i25]David Mueller, Nicholas Andrews, Mark Dredze:
Sources of Transfer in Multilingual Named Entity Recognition. CoRR abs/2005.00847 (2020) - [i24]Shijie Wu, Mark Dredze:
Are All Languages Created Equal in Multilingual BERT? CoRR abs/2005.09093 (2020) - [i23]David A. Broniatowski, Daniel Kerchner, Fouzia Farooq, Xiaolei Huang, Amelia M. Jamison, Mark Dredze, Sandra Crouse Quinn:
The COVID-19 Social Media Infodemic Reflects Uncertainty and State-Sponsored Propaganda. CoRR abs/2007.09682 (2020) - [i22]Shijie Wu, Mark Dredze:
Do Explicit Alignments Robustly Improve Multilingual Encoders? CoRR abs/2010.02537 (2020) - [i21]Aaron Mueller, Zach Wood-Doughty, Silvio Amir, Mark Dredze, Alicia L. Nobles:
Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement. CoRR abs/2010.06472 (2020) - [i20]Elliot Schumacher, James Mayfield, Mark Dredze:
Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking. CoRR abs/2010.09828 (2020) - [i19]Keith Harrigian, Carlos Aguirre, Mark Dredze:
On the State of Social Media Data for Mental Health Research. CoRR abs/2011.05233 (2020) - [i18]Rachel Dorn, Alicia L. Nobles, Masoud Rouhizadeh, Mark Dredze:
Examining the Feasibility of Off-the-Shelf Algorithms for Masking Directly Identifiable Information in Social Media Data. CoRR abs/2011.08324 (2020) - 2019
- [i17]Shijie Wu, Mark Dredze:
Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT. CoRR abs/1904.09077 (2019) - [i16]Andriy Mulyar, Elliot Schumacher, Masoud Rouhizadeh, Mark Dredze:
Phenotyping of Clinical Notes with Improved Document Classification Models Using Contextualized Neural Language Models. CoRR abs/1910.13664 (2019) - 2018
- [i15]Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent:
Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning. CoRR abs/1809.03684 (2018) - [i14]Zach Wood-Doughty, Ilya Shpitser, Mark Dredze:
Challenges of Using Text Classifiers for Causal Inference. CoRR abs/1810.00956 (2018) - 2017
- [i13]Ann Irvine, Mark Dredze:
Harmonic Grammar, Optimality Theory, and Syntax Learnability: An Empirical Exploration of Czech Word Order. CoRR abs/1702.05793 (2017) - [i12]Travis Wolfe, Mark Dredze, Benjamin Van Durme:
Feature Generation for Robust Semantic Role Labeling. CoRR abs/1702.07046 (2017) - 2016
- [i11]Nanyun Peng, Mark Dredze:
Learning Word Segmentation Representations to Improve Named Entity Recognition for Chinese Social Media. CoRR abs/1603.00786 (2016) - [i10]Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley:
Embedding Lexical Features via Low-Rank Tensors. CoRR abs/1604.00461 (2016) - [i9]Mark Dredze, Manuel García-Herranz, Alex Rutherford, Gideon Mann:
Twitter as a Source of Global Mobility Patterns for Social Good. CoRR abs/1606.06343 (2016) - [i8]Nanyun Peng, Mark Dredze:
Multi-task Multi-domain Representation Learning for Sequence Tagging. CoRR abs/1608.02689 (2016) - [i7]Adrian Benton, Braden Hancock, Glen Coppersmith, John W. Ayers, Mark Dredze:
After Sandy Hook Elementary: A Year in the Gun Control Debate on Twitter. CoRR abs/1610.02060 (2016) - [i6]John W. Ayers, Benjamin M. Althouse, Eric C. Leas, Ted Alcorn, Mark Dredze:
Can Big Media Data Revolutionarize Gun Violence Prevention? CoRR abs/1611.01148 (2016) - 2015
- [i5]Matthew R. Gormley, Mo Yu, Mark Dredze:
Improved Relation Extraction with Feature-rich Compositional Embedding Models. CoRR abs/1505.02419 (2015) - [i4]Travis Wolfe, Mark Dredze, James Mayfield, Paul McNamee, Craig Harman, Tim Finin, Benjamin Van Durme:
Interactive Knowledge Base Population. CoRR abs/1506.00301 (2015) - [i3]Matthew R. Gormley, Mark Dredze, Jason Eisner:
Approximation-Aware Dependency Parsing by Belief Propagation. CoRR abs/1508.02375 (2015) - 2013
- [i2]Damianos G. Karakos, Mark Dredze, Sanjeev Khudanpur:
Estimating Confusions in the ASR Channel for Improved Topic-based Language Model Adaptation. CoRR abs/1303.5148 (2013) - 2009
- [i1]Paul McNamee, Mark Dredze, Adam Gerber, Nikesh Garera, Tim Finin, James Mayfield, Christine D. Piatko, Delip Rao, David Yarowsky, Markus Dreyer:
HLTCOE Approaches to Knowledge Base Population at TAC 2009. TAC 2009
Coauthor Index
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