6 papers
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…
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…
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)…
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…