activity
20242026
most citedContrastive Prompt Clustering for Weakly Supervised Semantic Segmentation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Leveraging Adaptive Group Negotiation for Heterogeneous Multi-Robot Collaboration with Large Language Models

Siqi Song, Xuanbing Xie, Zonglin Li +3

Multi-robot collaboration tasks often require heterogeneous robots to work together over long horizons under spatial constraints and environmental uncertainties. Although Large Lan…

cs.CV20251 cited

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…

cs.IR2025

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…

cs.CV2025

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…

cs.IR2025

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…

cs.RO2024

Learning from Massive Human Videos for Universal Humanoid Pose Control

Jiageng Mao, Siheng Zhao, Siqi Song +7

Scalable learning of humanoid robots is crucial for their deployment in real-world applications. While traditional approaches primarily rely on reinforcement learning or teleoperat…