7 citations · 16 across the 15 of their papers we have counts for
5 papers · 1 filter
Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers
Qi Deng, Shuaicheng Niu, Ronghao Zhang +4
Test-time adaptation (TTA) aims to fine-tune a trained model online using unlabeled testing data to adapt to new environments or out-of-distribution data, demonstrating broad appli…
Understanding Emotional Body Expressions via Large Language Models
Haifeng Lu, Jiuyi Chen, Feng Liang +3
Emotion recognition based on body movements is vital in human-computer interaction. However, existing emotion recognition methods predominantly focus on enhancing classification ac…
Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning
Runhao Zeng, Dingjie Zhou, Qiwei Liang +6
Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large languag…
Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey
Feng Liang, Zhen Zhang, Haifeng Lu +4
With rapidly increasing distributed deep learning workloads in large-scale data centers, efficient distributed deep learning framework strategies for resource allocation and worklo…
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey
Feng Liang, Zhen Zhang, Haifeng Lu +3
With the rapid growth in the volume of data sets, models, and devices in the domain of deep learning, there is increasing attention on large-scale distributed deep learning. In con…