Xu, Wei

Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation

Zhou, J., Cao, Y., Wang, X., Li, P., & Xu, W. (2016) · Transactions of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 216

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Aremu, A., Bosselut, A., Chandu, K. R., Clinciu, M.-A., Das, D., Dhole, K., et al. (2021) · Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021)

Natural Language Processing TechniquesTopic Modeling

Cited by 159

Having Beer after Prayer? Measuring Cultural Bias in Large Language Models

Naous, T., Ryan, M. J., Ritter, A., & Xu, W. (2023) · arXiv

Topic ModelingEthics and Social Impacts of AI

Cited by 96

Having Beer after Prayer? Measuring Cultural Bias in Large Language Models

Naous, T., Ryan, M. J., Ritter, A., & Xu, W. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingEthics and Social Impacts of AI

Cited by 96

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Anuoluwapo, A., Bosselut, A., Chandu, K. R., Clinciu, M., Das, D., Dhole, K. D., et al. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 49

arXivEdits: Understanding the Human Revision Process in Scientific Writing

Jiang, C., Xu, W., & Stevens, S. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesAcademic Writing and Publishing

Cited by 18

FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence

Joseph, S., Chen, L., Trienes, J., Göke, H., Coers, M., Xu, W., Wallace, B., & Li, J. J. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Biomedical Text Mining and OntologiesText Readability and Simplification

Cited by 17

Identifying Metabolic Syndrome Easily and Cost Effectively Using Non-Invasive Methods with Machine Learning Models

Xu, W., Zhang, Z., Hu, K., Fang, P., Li, R., Kong, D., Xuan, M., Yue, Y., She, D., & Xue, Y. (2023) · Diabetes, Metabolic Syndrome and Obesity

Artificial Intelligence in HealthcareDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 9

Human-Centered Evaluation and Auditing of Language Models

Liu, Y. L., Deng, W. H., Lam, M. S., Eslami, M., Kim, J., Liao, Q. V., Xu, W., Novikova, J., & Xiao, Z. (2025) · Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 7