4 papers
ZOTTA: Test-Time Adaptation with Gradient-Free Zeroth-Order Optimization
Ronghao Zhang, Shuaicheng Niu, Qi Deng +3
Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods rely on backpropagation (BP), wh…
A Confidence-Constrained Cloud-Edge Collaborative Framework for Autism Spectrum Disorder Diagnosis
Qi Deng, Yinghao Zhang, Yalin Liu +1
Autism Spectrum Disorder (ASD) diagnosis systems in school environments increasingly relies on IoT-enabled cameras, yet pure cloud processing raises privacy and latency concerns wh…
Exploring Audio Cues for Enhanced Test-Time Video Model Adaptation
Runhao Zeng, Qi Deng, Ronghao Zhang +4
Test-time adaptation (TTA) aims to boost the generalization capability of a trained model by conducting self-/unsupervised learning during the testing phase. While most existing TT…
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…