3 papers
cs.IR2026
Climber-Pilot: A Non-Myopic Generative Recommendation Model Towards Better Instruction-Following
Da Guo, Shijia Wang, Qiang Xiao +7
Generative retrieval has emerged as a promising paradigm in recommender systems, offering superior sequence modeling capabilities over traditional dual-tower architectures. However…
cs.CV2026
YOLO-DS: Fine-Grained Feature Decoupling via Dual-Statistic Synergy Operator for Object Detection
Lin Huang, Yujuan Tan, Weisheng Li +6
One-stage object detection, particularly the YOLO series, strikes a favorable balance between accuracy and efficiency. However, existing YOLO detectors lack explicit modeling of he…
cs.CV2025
YOLO-PRO: Enhancing Instance-Specific Object Detection with Full-Channel Global Self-Attention
Lin Huang, Yujuan Tan, Weisheng Li +5
This paper addresses the inherent limitations of conventional bottleneck structures (diminished instance discriminability due to overemphasis on batch statistics) and decoupled hea…