Wang, Xuezhi

PaLM: Scaling Language Modeling with Pathways

Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,590

Scaling Instruction-Finetuned Language Models

Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1,441

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

PaLM 2 Technical Report

Anil, R., Dai, A. M., Firat, O., Johnson, M., Lepikhin, D., Passos, A., Shakeri, S., Taropa, E., Bailey, P., Chen, Z., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 834

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Wang, X., Wei, J., Schuurmans, D., Le, Q., Chi, E., Narang, S., Chowdhery, A., & Zhou, D. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 829

Underspecification Presents Challenges for Credibility in Modern Machine Learning

D'Amour, A., Heller, K., Moldovan, D., Adlam, B., Alipanahi, B., Beutel, A., Chen, C., Deaton, J., Eisenstein, J., Hoffman, M. D., et al. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 398

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Zhou, D., Schärli, N., Hou, L., Wei, J., Scales, N., Wang, X., Schuurmans, D., Cui, C., Bousquet, O., Le, Q., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 380

Large Language Models Can Self-Improve

Huang, J., Gu, S. S., Hou, L., Wu, Y., Wang, X., Yu, H., & Han, J. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 230

Large Language Models Can Self-Improve

Huang, J., Gu, S., Hou, L., Wu, Y., Wang, X., Yu, H., & Han, J. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 230

Measuring and Reducing Gendered Correlations in Pre-trained Models

Webster, K., Wang, X., Tenney, I., Beutel, A., Pitler, E., Pavlick, E., Chen, J., Chi, E., & Petrov, S. (2020) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 195

Large Language Models as Optimizers

Yang, C., Wang, X., Lu, Y., Liu, H., Le, Q. V., Zhou, D., & Chen, X. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 151

Measure and Improve Robustness in NLP Models: A Survey

Wang, X., Wang, H., & Yang, D. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 90

Continual Learning for Text Classification with Information Disentanglement Based Regularization

Huang, Y., Zhang, Y., Chen, J., Wang, X., & Yang, D. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 74

Language Models are Multilingual Chain-of-Thought Reasoners

Shi, F., Suzgun, M., Freitag, M., Wang, X., Srivats, S., Vosoughi, S., Chung, H. W., Tay, Y., Ruder, S., Zhou, D., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 60

Chain-of-Thought Reasoning Without Prompting

Wang, X., & Zhou, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 54

Recitation-Augmented Language Models

Sun, Z., Wang, X., Tay, Y., Yang, Y., & Zhou, D. (2022) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 34

Large language models as tool makers

Cai, T., Wang, X., Ma, T., Chen, X., & Zhou, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 28

Universal Self-Consistency for Large Language Model Generation

Chen, X., Aksitov, R., Alon, U., Ren, J., Xiao, K., Yin, P., Prakash, S., Sutton, C., Wang, X., & Zhou, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 13

Premise Order Matters in Reasoning with Large Language Models

Chen, X., Chi, R. A., Wang, X., & Zhou, D. (2024) · arXiv

Topic ModelingLogic, Reasoning, and Knowledge

Cited by 3