3 citations · 3 across the 3 of their papers we have counts for
4 papers
Progressive Prompt-Guided Cross-Modal Reasoning for Referring Image Segmentation
Jiachen Li, Hongyun Wang, Jinyu Xu +5
Referring image segmentation aims to localize and segment a target object in an image based on a free-form referring expression. The core challenge lies in effectively bridging lin…
KGBridge: Knowledge-Guided Prompt Learning for Non-overlapping Cross-Domain Recommendation
Yuhan Wang, Qing Xie, Zhifeng Bao +3
Knowledge Graphs (KGs), as structured knowledge bases that organize relational information across diverse domains, provide a unified semantic foundation for cross-domain recommenda…
Enhancing Transferability and Consistency in Cross-Domain Recommendations via Supervised Disentanglement
Yuhan Wang, Qing Xie, Zhifeng Bao +3
Cross-domain recommendation (CDR) aims to alleviate the data sparsity by transferring knowledge across domains. Disentangled representation learning provides an effective solution…
LGD: Leveraging Generative Descriptions for Zero-Shot Referring Image Segmentation
Jiachen Li, Qing Xie, Renshu Gu +3
Zero-shot referring image segmentation aims to locate and segment the target region based on a referring expression, with the primary challenge of aligning and matching semantics a…