3 papers
cs.CV2025
Collaborative Learning for Enhanced Unsupervised Domain Adaptation
Minhee Cho, Hyesong Choi, Hayeon Jo +1
Unsupervised Domain Adaptation (UDA) endeavors to bridge the gap between a model trained on a labeled source domain and its deployment in an unlabeled target domain. However, curre…
cs.CV2025
iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation
Hayeon Jo, Hyesong Choi, Minhee Cho +1
Transfer learning based on full fine-tuning (FFT) of the pre-trained encoder and task-specific decoder becomes increasingly complex as deep models grow exponentially. Parameter eff…
cs.CV2025
TADFormer : Task-Adaptive Dynamic Transformer for Efficient Multi-Task Learning
Seungmin Baek, Soyul Lee, Hayeon Jo +2
Transfer learning paradigm has driven substantial advancements in various vision tasks. However, as state-of-the-art models continue to grow, classical full fine-tuning often becom…