6 papers
ProtoFlow: Mitigating Forgetting in Class-Incremental Remote Sensing Segmentation via Low-Curvature Prototype Flow
Jiekai Wu, Rong Fu, Chuangqi Li +10
Remote sensing segmentation in real deployment is inherently continual: new semantic categories emerge, and acquisition conditions shift across seasons, cities, and sensors. Despit…
DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection
Siheng Wang, Yanshu Li, Bohan Hu +12
Open-vocabulary object detection (OVOD) enables models to recognize objects beyond predefined categories, but existing approaches remain limited in practical deployment. On the one…
EGAD: Entropy-Guided Adaptive Distillation for Token-Level Knowledge Transfer
Hao Zhang, Zhibin Zhang, Guangxin Wu +3
Large language models (LLMs) have achieved remarkable performance across diverse domains, yet their enormous computational and memory requirements hinder deployment in resource-con…
ConsRoute:Consistency-Aware Adaptive Query Routing for Cloud-Edge-Device Large Language Models
Haoyu Qiao, Hao Zhang, Shanwen Mao +2
Large language models (LLMs) deliver impressive capabilities but incur substantial inference latency and cost, which hinders their deployment in latency-sensitive and resource-cons…
MI-PRUN: Optimize Large Language Model Pruning via Mutual Information
Hao Zhang, Zhibin Zhang, Guangxin Wu +3
Large Language Models (LLMs) have become indispensable across various domains, but this comes at the cost of substantial computational and memory resources. Model pruning addresses…
Iterative Structured Pruning for Large Language Models with Multi-Domain Calibration
Guangxin Wu, Hao Zhang, Zhang Zhibin +2
Large Language Models (LLMs) have achieved remarkable success across a wide spectrum of natural language processing tasks. However, their ever-growing scale introduces significant…