| Causal inference in natural language processing: Estimation, prediction, interpretation and beyond A Feder, KA Keith, E Manzoor, R Pryzant, D Sridhar, Z Wood-Doughty, ... Transactions of the Association for Computational Linguistics 10, 1138-1158, 2022 | 263 | 2022 |
| Vaccine-related advertising in the Facebook Ad Archive AM Jamison, DA Broniatowski, M Dredze, Z Wood-Doughty, DA Khan, ... Vaccine 38 (3), 512-520, 2020 | 110 | 2020 |
| Challenges of Using Text Classifiers for Causal Inference Z Wood-Doughty, I Shpitser, M Dredze Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 89 | 2018 |
| Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement A Mueller, Z Wood-Doughty, S Amir, M Dredze, AL Nobles Proceedings of the ACM on Human-Computer Interaction 5 (CSCW1), 1-28, 2021 | 69 | 2021 |
| Predicting Twitter User Demographics from Names Alone Z Wood-Doughty, N Andrews, R Marvin, M Dredze Proceedings of the Second Workshop on Computational Modeling of People’s …, 2018 | 57 | 2018 |
| How Does Twitter User Behavior Vary Across Demographic Groups? Z Wood-Doughty, M Smith, D Broniatowski, M Dredze Proceedings of the Second Workshop on NLP and Computational Social Science …, 2017 | 35 | 2017 |
| Johns Hopkins or johnny-hopkins: Classifying Individuals versus Organizations on Twitter Z Wood-Doughty, P Mahajan, M Dredze Proceedings of the Second Workshop on Computational Modeling of People’s …, 2018 | 33 | 2018 |
| Vaccine opponents' use of Twitter during the 2016 US presidential election: Implications for practice and policy. M Dredze, Z Wood-Doughty, SC Quinn, DA Broniatowski Vaccine 35 (36), 4670-4672, 2017 | 30 | 2017 |
| Using Noisy Self-Reports to Predict Twitter User Demographics Z Wood-Doughty, P Xu, X Liu, M Dredze SocialNLP 2021, 123, 2020 | 23 | 2020 |
| The proximal id algorithm I Shpitser, Z Wood-Doughty, EJT Tchetgen Journal of Machine Learning Research 24 (188), 1-46, 2023 | 18 | 2023 |
| Leveraging machine learning to predict 30-day hospital readmission after cardiac surgery E Sherman, D Alejo, Z Wood-Doughty, M Sussman, S Schena, CS Ong, ... The Annals of Thoracic Surgery 114 (6), 2173-2179, 2022 | 16 | 2022 |
| Segment anything model is a good teacher for local feature learning J Wu, R Xu, Z Wood-Doughty, C Wang, S Xu, EY Lam arXiv preprint arXiv:2309.16992, 2023 | 13 | 2023 |
| Model Distillation for Faithful Explanations of Medical Code Predictions Z Wood-Doughty, I Cachola, M Dredze Proceedings of the 21st Workshop on Biomedical Language Processing, 412-425, 2022 | 13* | 2022 |
| Generating Synthetic Text Data to Evaluate Causal Inference Methods Z Wood-Doughty, I Shpitser, M Dredze arXiv preprint arXiv:2102.05638, 2021 | 13 | 2021 |
| Convolutions Are All You Need (For Classifying Character Sequences) Z Wood-Doughty, N Andrews, M Dredze Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User …, 2018 | 13 | 2018 |
| Audio-Journey: Efficient Visual+ LLM-aided Audio Encodec Diffusion JB Li, JS Michaels, L Yao, L Yu, Z Wood-Doughty, F Metze Workshop on Efficient Systems for Foundation Models@ ICML2023, 2023 | 8 | 2023 |
| Proxy Model Explanations for Time Series RNNs Z Wood-Doughty, I Cachola, M Dredze 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 4 | 2021 |
| Audio-Journey: Open Domain Latent Diffusion Based Text-To-Audio Generation J Michaels, JB Li, L Yao, L Yu, Z Wood-Doughty, F Metze ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 3 | 2024 |
| Reliability of Topic Modeling K Schroeder, Z Wood-Doughty arXiv preprint arXiv:2410.23186, 2024 | 1 | 2024 |
| DoubleLingo: Causal Estimation with Large Language Models M Veljanovski, Z Wood-Doughty Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | 1 | 2024 |