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cs.CV2026
CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations
Chengfeng Wu, Tao Zou, Yanru Wu +1
Multi-task learning (MTL) aims to construct a joint model for multiple tasks by sharing a common representation across domains. To achieve this goal, existing optimization-centric…
cs.CV2026
Guided Prompt Evolution for Vision-Language Models Adaptation
Enming Zhang, Jiayang Li, Yanlong Wang +3
The adaptation of large-scale vision-language models (VLMs) to downstream tasks with limited labeled data remains a significant challenge. While parameter-efficient prompt learning…
cs.CV2025
TMT: Cross-domain Semantic Segmentation with Region-adaptive Transferability Estimation
Enming Zhang, Zhengyu Li, Yanru Wu +5
Recent advances in Vision Transformers (ViTs) have significantly advanced semantic segmentation performance. However, their adaptation to new target domains remains challenged by d…