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20212024
most citedThe Rise and Potential of Large Language Model Based Agents: A Survey

256 citations · 302 across the 13 of their papers we have counts for

collaborators

5 papers

cs.AI2023256 cited

The Rise and Potential of Large Language Model Based Agents: A Survey

Zhiheng Xi, Wenxiang Chen, Xin Guo +26

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI a…

cs.DC2023

Federated cINN Clustering for Accurate Clustered Federated Learning

Yuhao Zhou, Minjia Shi, Yuxin Tian +3

Federated Learning (FL) presents an innovative approach to privacy-preserving distributed machine learning and enables efficient crowd intelligence on a large scale. However, a sig…

cs.IT2023

Interpreting Training Aspects of Deep-Learned Error-Correcting Codes

N. Devroye, A. Mulgund, R. Shekhar +3

As new deep-learned error-correcting codes continue to be introduced, it is important to develop tools to interpret the designed codes and understand the training process. Prior wo…

cs.LG2023

Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence

Yuhao Zhou, Mingjia Shi, Yuanxi Li +3

Reducing communication overhead in federated learning (FL) is challenging but crucial for large-scale distributed privacy-preserving machine learning. While methods utilizing spars…

stat.AP2021

Robust Online Detection in Serially Correlated Directed Network

Miaomiao Yu, Yuhao Zhou, Fugee Tsung

As the complexity of production processes increases, the diversity of data types drives the development of network monitoring technology. This paper mainly focuses on an online alg…