6 papers
LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendation
Wangyu Wu, Zhenhong Chen, Wenqiao Zhang +5
Cross-Domain Sequential Recommendation (CDSR) predicts user behavior by leveraging historical interactions across multiple domains, focusing on modeling cross-domain preferences an…
Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation
Wangyu Wu, Zhenhong Chen, Xiaowen Ma +6
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained attention for its cost-effectiveness. Most existing methods emphasize inter-class separation, ofte…
Cognitive-Inspired Hierarchical Attention Fusion With Visual and Textual for Cross-Domain Sequential Recommendation
Wangyu Wu, Zhenhong Chen, Siqi Song +4
Cross-Domain Sequential Recommendation (CDSR) predicts user behavior by leveraging historical interactions across multiple domains, focusing on modeling cross-domain preferences th…
Image Augmentation Agent for Weakly Supervised Semantic Segmentation
Wangyu Wu, Xianglin Qiu, Siqi Song +4
Weakly-supervised semantic segmentation (WSSS) has achieved remarkable progress using only image-level labels. However, most existing WSSS methods focus on designing new network st…
Prompt Categories Cluster for Weakly Supervised Semantic Segmentation
Wangyu Wu, Xianglin Qiu, Siqi Song +3
Weakly Supervised Semantic Segmentation (WSSS), which leverages image-level labels, has garnered significant attention due to its cost-effectiveness. The previous methods mainly st…
Image Fusion for Cross-Domain Sequential Recommendation
Wangyu Wu, Siqi Song, Xianglin Qiu +3
Cross-Domain Sequential Recommendation (CDSR) aims to predict future user interactions based on historical interactions across multiple domains. The key challenge in CDSR is effect…