activity
20162023
most cited6G Internet of Things: A Comprehensive Survey

1.4k citations · 2.6k across the 41 of their papers we have counts for

collaborators

41 papers

cs.LG2023★ 4 cited

Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

Shiying Zhang, Jun Li, Long Shi +5

Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT). Nonetheles…

cs.LG2023★ 10 cited

GPT Can Solve Mathematical Problems Without a Calculator

Zhen Yang, Ming Ding, Qingsong Lv +5

Previous studies have typically assumed that large language models are unable to accurately perform arithmetic operations, particularly multiplication of >8 digits, and operations…

cs.LG2023

Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity

Xuefeng Han, Jun Li, Wen Chen +4

With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely considered for application in wireless networks for distributed model training. Howeve…

cs.DC2023

Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning

Kecheng Fan, Wen Chen, Jun Li +3

As an efficient distributed machine learning approach, Federated learning (FL) can obtain a shared model by iterative local model training at the user side and global model aggrega…

cs.CV2023★ 1 cited

R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut

Yingjie Niu, Ming Ding, Maoning Ge +3

Transformer-based models have gained popularity in the field of natural language processing (NLP) and are extensively utilized in computer vision tasks and multi-modal models such…

cs.CV2023

Boosting Long-tailed Object Detection via Step-wise Learning on Smooth-tail Data

Na Dong, Yongqiang Zhang, Mingli Ding +1

Real-world data tends to follow a long-tailed distribution, where the class imbalance results in dominance of the head classes during training. In this paper, we propose a frustrat…