4 citations · 10 across the 14 of their papers we have counts for
4 papers · 1 filter
Sample-aware Adaptive Structured Pruning for Large Language Models
Jun Kong, Xinge Ma, Jin Wang +1
Large language models (LLMs) have achieved outstanding performance in natural language processing, but enormous model sizes and high computational costs limit their practical deplo…
Vision-aware Multimodal Prompt Tuning for Uploadable Multi-source Few-shot Domain Adaptation
Kuanghong Liu, Jin Wang, Kangjian He +2
Conventional multi-source domain few-shot adaptation (MFDA) faces the challenge of further reducing the load on edge-side devices in low-resource scenarios. Considering the native…
Multi-Attribute Multi-Grained Adaptation of Pre-Trained Language Models for Text Understanding from Bayesian Perspective
You Zhang, Jin Wang, Liang-Chih Yu +2
Current neural networks often employ multi-domain-learning or attribute-injecting mechanisms to incorporate non-independent and identically distributed (non-IID) information for te…
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation
Xinge Ma, Jin Wang, Xuejie Zhang
Federated learning (FL) enables decentralized clients to collaboratively train a global model under the orchestration of a central server without exposing their individual data. Ho…