Large Language Models Can Be Used to Estimate the Latent Positions of Politicians PY Wu, J Nagler, JA Tucker, S Messing | 34 | 2023 |
MARMOT: A deep learning framework for constructing multimodal representations for vision-and-language tasks PY Wu, WR Mebane Jr Computational Communication Research 4 (1), 2022 | 18 | 2022 |
Using twitter to observe election incidents in the united states WR Mebane Jr, A Pineda, L Woods, J Klaver, P Wu, B Miller Annual meeting of the midwest political science association, chicago, 2017 | 11 | 2017 |
Partisan associations of Twitter users based on their self-descriptions and word embeddings PY Wu, WR Mebane Jr, L Woods, J Klaver, P Due 2019 Annual Meeting of the American Political Science Association (APSA 2019), 2019 | 10 | 2019 |
Observing Election Incidents in the United States via Twitter: Does Who Observes Matter? WR Mebane Jr, P Wu, L Woods, J Klaver, A Pineda, B Miller Annual Meeting of the Midwest Political Science Association, Chicago, 2018 | 9 | 2018 |
Measuring Election Frauds WR Mebane Jr, D Ferrari, K McAlister, PY Wu | 5 | 2022 |
Concept-Guided Chain-of-Thought Prompting for Pairwise Comparison Scaling of Texts with Large Language Models PY Wu, J Nagler, JA Tucker, S Messing arXiv preprint arXiv:2310.12049, 2023 | 1 | 2023 |
Dictionary-Assisted Supervised Contrastive Learning PY Wu, R Bonneau, JA Tucker, J Nagler arXiv preprint arXiv:2210.15172, 2022 | 1 | 2022 |