Wang, Xing

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Shi, S., & Tu, Z. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 1,062

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Shi, S., & Tu, Z. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 320

ProtoHAR: Prototype Guided Personalized Federated Learning for Human Activity Recognition

Cheng, D., Zhang, L., Bu, C., Wang, X., Wu, H., & Song, A. (2023) · IEEE Journal of Biomedical and Health Informatics

Privacy-Preserving Technologies in DataContext-Aware Activity Recognition Systems

Cited by 92

Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models

He, Z., Zhou, B., Hao, H., Liu, A., Wang, X., Tu, Z., Zhang, Z., & Wang, R. (2024) · arXiv

Advanced Steganography and Watermarking TechniquesAdversarial Robustness in Machine Learning

Cited by 3