Ye Yuan

According to our database, Ye Yuan authored at least 15 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities.

Hao Zhou, Chengming Hu, Ye Yuan, Yufei Cui, Yili Jin, Can Chen, Haolun Wu, Dun Yuan, Li Jiang, Di Wu, Xue (Steve) Liu, Jianzhong Zhang, Xianbin Wang, Jiangchuan Liu

IEEE Commun. Surv. Tutorials, June, 2025

Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain.

Ye Yuan, Haolun Wu, Hao Zhou, Xue Liu, Hao Chen, Yan Xin, Jianzhong Zhang

CoRR, May, 2025

Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-Context Learning.

Hao Zhou, Chengming Hu, Dun Yuan, Ye Yuan, Di Wu, Xue Liu, Zhu Han, Jianzhong Zhang

IEEE Wirel. Commun. Lett., March, 2025

Offline Model-Based Optimization: Comprehensive Review.

Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, Can Chen

CoRR, March, 2025

Design Editing for Offline Model-based Optimization.

Ye Yuan, Youyuan Zhang, Can Chen, Haolun Wu, Melody Zixuan Li, Jianmo Li, James J. Clark, Xue Liu

Trans. Mach. Learn. Res., 2025

ParetoFlow: Guided Flows in Multi-Objective Optimization.

Ye Yuan, Can Chen, Christopher Pal, Xue Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Large Language Models (LLMs) for Wireless Networks: An Overview from the Prompt Engineering Perspective.

Hao Zhou, Chengming Hu, Dun Yuan, Ye Yuan, Di Wu, Xi Chen, Hina Tabassum, Xue Liu

CoRR, 2024

Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-context Learning.

Hao Zhou, Chengming Hu, Dun Yuan, Ye Yuan, Di Wu, Xue Liu, Zhu Han, Charlie Zhang

CoRR, 2024

Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control.

Hao Zhou, Chengming Hu, Dun Yuan, Ye Yuan, Di Wu, Xue Liu, Charlie Jianzhong Zhang

CoRR, 2024

Retrieval-Augmented Generation for Natural Language Processing: A Survey.

Shangyu Wu, Ying Xiong, Yufei Cui, Haolun Wu, Can Chen, Ye Yuan, Lianming Huang, Xue Liu, Tei-Wei Kuo, Nan Guan, Chun Jason Xue

CoRR, 2024

Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities.

Hao Zhou, Chengming Hu, Ye Yuan, Yufei Cui, Yili Jin, Can Chen, Haolun Wu, Dun Yuan, Li Jiang, Di Wu, Xue Liu, Charlie Jianzhong Zhang, Xianbin Wang, Jiangchuan Liu

CoRR, 2024

Structured Entity Extraction Using Large Language Models.

Haolun Wu, Ye Yuan, Liana Mikaelyan, Alexander Meulemans, Xue Liu, James Hensman, Bhaskar Mitra

CoRR, 2024

Learning to Extract Structured Entities Using Language Models.

Haolun Wu, Ye Yuan, Liana Mikaelyan, Alexander Meulemans, Xue Liu, James Hensman, Bhaskar Mitra

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Importance-aware Co-teaching for Offline Model-based Optimization.

Ye Yuan, Can Chen, Zixuan Liu, Willie Neiswanger, Xue (Steve) Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Towards Auditing the Sensitive Information Leakage During Data Trading and Data Computing.

Shuhao Zheng, Yanxi Lin, Yang Yu, Ye Yuan, Yongzheng Jia, Xue Liu

CoRR, 2022