2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2025★ 2 cited
COLA: Context-aware Language-driven Test-time Adaptation
Aiming Zhang, Tianyuan Yu, Liang Bai +5
Test-time adaptation (TTA) has gained increasing popularity due to its efficacy in addressing ``distribution shift'' issue while simultaneously protecting data privacy. However, mo…
cs.AI2024★ 1 cited
Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective
Yujie Mo, Zhihe Lu, Runpeng Yu +2
Self-supervised heterogeneous graph learning (SHGL) has shown promising potential in diverse scenarios. However, while existing SHGL methods share a similar essential with clusteri…
cs.CV2024
Dual-Path Adversarial Lifting for Domain Shift Correction in Online Test-time Adaptation
Yushun Tang, Shuoshuo Chen, Zhihe Lu +2
Transformer-based methods have achieved remarkable success in various machine learning tasks. How to design efficient test-time adaptation methods for transformer models becomes an…