5 papers
ICM-Fusion: In-Context Meta-Optimized LoRA Fusion for Multi-Task Adaptation
Yihua Shao, Xiaofeng Lin, Xinwei Long +7
Enabling multi-task adaptation in pre-trained Low-Rank Adaptation (LoRA) models is crucial for enhancing their generalization capabilities. Most existing pre-trained LoRA fusion me…
EventVAD: Training-Free Event-Aware Video Anomaly Detection
Yihua Shao, Haojin He, Sijie Li +11
Video Anomaly Detection~(VAD) focuses on identifying anomalies within videos. Supervised methods require an amount of in-domain training data and often struggle to generalize to un…
MambaIC: State Space Models for High-Performance Learned Image Compression
Fanhu Zeng, Hao Tang, Yihua Shao +3
A high-performance image compression algorithm is crucial for real-time information transmission across numerous fields. Despite rapid progress in image compression, computational…
In-Context Meta LoRA Generation
Yihua Shao, Minxi Yan, Yang Liu +12
Low-rank Adaptation (LoRA) has demonstrated remarkable capabilities for task specific fine-tuning. However, in scenarios that involve multiple tasks, training a separate LoRA model…
GWQ: Gradient-Aware Weight Quantization for Large Language Models
Yihua Shao, Yan Gu, Siyu Chen +12
Large language models (LLMs) show impressive performance in solving complex language tasks. However, its large number of parameters presents significant challenges for the deployme…