5 citations · 12 across the 12 of their papers we have counts for
12 papers
Private Transformer Inference in MLaaS: A Survey
Yang Li, Xinyu Zhou, Yitong Wang +2
Transformer models have revolutionized AI, powering applications like content generation and sentiment analysis. However, their deployment in Machine Learning as a Service (MLaaS)…
Kimi-VL Technical Report
Kimi Team, Angang Du, Bohong Yin +92
We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…
FedSem: A Resource Allocation Scheme for Federated Learning Assisted Semantic Communication
Xinyu Zhou, Yang Li, Jun Zhao
Semantic communication (SemCom), regarded as the evolution of the traditional Shannon's communication model, stresses the transmission of semantic information instead of the data i…
Resource Allocation for the Training of Image Semantic Communication Networks
Yang Li, Xinyu Zhou, Jun Zhao
Semantic communication is a new paradigm that aims at providing more efficient communication for the next-generation wireless network. It focuses on transmitting extracted, meaning…
A Survey on Private Transformer Inference
Yang Li, Xinyu Zhou, Yitong Wang +2
Transformer models have revolutionized AI, enabling applications like content generation and sentiment analysis. However, their use in Machine Learning as a Service (MLaaS) raises…
Resource Allocation for Semantic Communication under Physical-layer Security
Yang Li, Xinyu Zhou, Jun Zhao
Semantic communication is deemed as a revolution of Shannon's paradigm in the six-generation (6G) wireless networks. It aims at transmitting the extracted information rather than t…
Optimizing Utility-Energy Efficiency for the Metaverse over Wireless Networks under Physical Layer Security
Jun Zhao, Xinyu Zhou, Yang Li +1
The Metaverse, an emerging digital space, is expected to offer various services mirroring the real world. Wireless communications for mobile Metaverse users should be tailored to m…
Resource Allocation of Federated Learning Assisted Mobile Augmented Reality System in the Metaverse
Xinyu Zhou, Yang Li, Jun Zhao
Metaverse has become a buzzword recently. Mobile augmented reality (MAR) is a promising approach to providing users with an immersive experience in the Metaverse. However, due to l…
Mobile Augmented Reality with Federated Learning in the Metaverse
Xinyu Zhou, Jun Zhao
The Metaverse is deemed the next evolution of the Internet and has received much attention recently. Metaverse applications via mobile augmented reality (MAR) require rapid and acc…
Resource Allocation of Federated Learning for the Metaverse with Mobile Augmented Reality
Xinyu Zhou, Chang Liu, Jun Zhao
The Metaverse has received much attention recently. Metaverse applications via mobile augmented reality (MAR) require rapid and accurate object detection to mix digital data with t…
Joint Optimization of Energy Consumption and Completion Time in Federated Learning
Xinyu Zhou, Jun Zhao, Huimei Han +1
Federated Learning (FL) is an intriguing distributed machine learning approach due to its privacy-preserving characteristics. To balance the trade-off between energy and execution…
A New Learning Paradigm for Stochastic Configuration Network: SCN+
Yanshuang Ao, Xinyu Zhou, Wei Dai
Learning using privileged information (LUPI) paradigm, which pioneered teacher-student interaction mechanism, makes the learning models use additional information in training stage…