Htut, Phu Mon

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

BBQ: A Hand-Built Bias Benchmark for Question Answering

Parrish, A., Chen, A., Nangia, N., Padmakumar, V., Phang, J., Thompson, J., Htut, P. M., & Bowman, S. R. (2021) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 189

BBQ: A hand-built bias benchmark for question answering

Parrish, A., Chen, A., Nangia, N., Padmakumar, V., Phang, J., Thompson, J., Htut, P. M., & Bowman, S. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Ethics and Social Impacts of AITopic Modeling

Cited by 186

Comparing Test Sets with Item Response Theory

Vania, C., Htut, P. M., Huang, W., Mungra, D., Pang, R. Y., Phang, J., Liu, H., Cho, K., & Bowman, S. R. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 18