3 papers
cs.CV2025
Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining
Qi Fan, Kaiqi Liu, Nian Liu +4
Cross-domain few-shot segmentation (CD-FSS) aims to segment objects of novel classes in new domains, which is often challenging due to the diverse characteristics of target domains…
cs.CV2025
E2MPL:An Enduring and Efficient Meta Prompt Learning Framework for Few-shot Unsupervised Domain Adaptation
Wanqi Yang, Haoran Wang, Lei Wang +3
Few-shot unsupervised domain adaptation (FS-UDA) leverages a limited amount of labeled data from a source domain to enable accurate classification in an unlabeled target domain. De…
cs.AI2025
Domain Generalizable Knowledge Tracing via Concept Aggregation and Relation-Based Attention
Yuquan Xie, Shengtao Peng, Wanqi Yang +2
Knowledge Tracing (KT) is a critical task in online education systems, aiming to monitor students' knowledge states throughout a learning period. Common KT approaches involve predi…