48 citations · 60 across the 5 of their papers we have counts for
6 papers
Learning to Communicate with Intent: An Introduction
Miguel Angel Gutierrez-Estevez, Yiqun Wu, Chan Zhou
We propose a novel framework to learn how to communicate with intent, i.e., to transmit messages over a wireless communication channel based on the end-goal of the communication. T…
Respecting Transfer Gap in Knowledge Distillation
Yulei Niu, Long Chen, Chang Zhou +1
Knowledge distillation (KD) is essentially a process of transferring a teacher model's behavior, e.g., network response, to a student model. The network response serves as addition…
Causal Attention for Unbiased Visual Recognition
Tan Wang, Chang Zhou, Qianru Sun +1
Attention module does not always help deep models learn causal features that are robust in any confounding context, e.g., a foreground object feature is invariant to different back…
QoS Prediction for 5G Connected and Automated Driving
Apostolos Kousaridas, Ramya Panthangi Manjunath, Jose Mauricio Perdomo +4
5G communication system can support the demanding quality-of-service (QoS) requirements of many advanced vehicle-to-everything (V2X) use cases. However, the safe and efficient driv…
M6: A Chinese Multimodal Pretrainer
Junyang Lin, Rui Men, An Yang +22
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1.9TB images and 292GB texts that cover a wide range of domains. We pro…
Block Compressed Sensing Based Distributed Device Detection for M2M Communications
Yunyan Chang, Peter Jung, Chan Zhou +1
In this work, we utilize the framework of compressed sensing (CS) for distributed device detection and resource allocation in large-scale machine-to-machine (M2M) communication net…