How Does Twitter User Behavior Vary Across Demographic Groups? - Zach Wood-Doughty; Michael Smith; David A. Broniatowski; Mark Dredze (NLP+CSS@ACL, 2017)

Predicting Twitter User Demographics from Names Alone. - Zach Wood-Doughty; Nicholas Andrews; Rebecca Marvin; Mark Dredze (PEOPLES@NAACL-HTL, 2018)

Johns Hopkins or johnny-hopkins: Classifying Individuals versus Organizations on Twitter. - Zach Wood-Doughty; Praateek Mahajan; Mark Dredze (PEOPLES@NAACL-HTL, 2018)

Convolutions Are All You Need (For Classifying Character Sequences). - Zach Wood-Doughty; Nicholas Andrews; Mark Dredze (NUT@EMNLP, 2018)

Challenges of Using Text Classifiers for Causal Inference. - Zach Wood-Doughty; Ilya Shpitser; Mark Dredze (EMNLP, 2018)

Using Noisy Self-Reports to Predict Twitter User Demographics. - Zach Wood-Doughty; Paiheng Xu; Xiao Liu; Mark Dredze (SocialNLP@NAACL, 2021)

Proxy Model Explanations for Time Series RNNs. - Zach Wood-Doughty; Isabel Cachola; Mark Dredze (ICMLA, 2021)

Generating Synthetic Text Data to Evaluate Causal Inference Methods. - Zach Wood-Doughty; Ilya Shpitser; Mark Dredze (CoRR, 2021)

Faithful and Plausible Explanations of Medical Code Predictions. - Zach Wood-Doughty; Isabel Cachola; Mark Dredze (CoRR, 2021)

Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement. - Aaron Mueller; Zach Wood-Doughty; Silvio Amir; Mark Dredze; Alicia Lynn Nobles (Proc. ACM Hum. Comput. Interact., 2021)

Model Distillation for Faithful Explanations of Medical Code Predictions. - Zach Wood-Doughty; Isabel Cachola; Mark Dredze (BioNLP@ACL, 2022)

Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. - Amir Feder; Katherine A. Keith; Emaad Manzoor; Reid Pryzant; Dhanya Sridhar; Zach Wood-Doughty; Jacob Eisenstein; Justin Grimmer; Roi Reichart; Margaret E. Roberts; Brandon M. Stewart; Victor Veitch; et al. (Trans. Assoc. Comput. Linguistics, 2022)

Segment Anything Model is a Good Teacher for Local Feature Learning. - Jingqian Wu; Rongtao Xu; Zach Wood-Doughty; Changwei Wang 001 (CoRR, 2023)

The Proximal ID Algorithm. - Ilya Shpitser; Zach Wood-Doughty; Eric J. Tchetgen Tchetgen (J. Mach. Learn. Res., 2023)

Audio-Journey: Open Domain Latent Diffusion Based Text-To-Audio Generation. - Jackson Michaels; Juncheng B. Li; Laura Yao; Lijun Yu; Zach Wood-Doughty; Florian Metze (ICASSP, 2024)

DoubleLingo: Causal Estimation with Large Language Models. - Marko Veljanovski; Zach Wood-Doughty (NAACL (Short Papers), 2024)

Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status. - Samuel Lee; Zach Wood-Doughty (CoRR, 2024)

Can You Trust LLM Judgments? Reliability of LLM-as-a-Judge. - Kayla Schroeder; Zach Wood-Doughty (CoRR, 2024)

Reliability of Topic Modeling. - Kayla Schroeder; Zach Wood-Doughty (NAACL (Long Papers), 2025)

Segment Anything Model Is a Good Teacher for Local Feature Learning. - Jingqian Wu; Rongtao Xu; Zach Wood-Doughty; Changwei Wang 001; Shibiao Xu; Edmund Y. Lam (IEEE Trans. Image Process., 2025)

Don't Forget It! Conditional Sparse Autoencoder Clamping Works for Unlearning. - Matthew Khoriaty; Andrii Shportko; Gustavo Mercier; Zach Wood-Doughty (CoRR, 2025)