8 citations · 14 across the 5 of their papers we have counts for
6 papers
FreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation
Zekun Shi, Alastair James Arthur Price
Linear-time sequence models typically store long-context information in a recurrent state. A fixed-size state limits how much information can be stored, while hybrid architectures…
An Empirical Study of Federated Prompt Learning for Vision Language Model
Zhihao Wang, Wenke Huang, Tian Chen +7
The Vision Language Model (VLM) excels in aligning vision and language representations, and prompt learning has emerged as a key technique for adapting such models to downstream ta…
Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model
Wenke Huang, Jian Liang, Xianda Guo +14
Multi-modal Large Language Models (MLLMs) integrate visual and linguistic reasoning to address complex tasks such as image captioning and visual question answering. While MLLMs dem…
Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi +6
Multimodal Large Language Model (MLLM) have demonstrated strong generalization capabilities across diverse distributions and tasks, largely due to extensive pre-training datasets.…
Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark
Wenke Huang, Mang Ye, Zekun Shi +4
Federated learning has emerged as a promising paradigm for privacy-preserving collaboration among different parties. Recently, with the popularity of federated learning, an influx…
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning
Wenke Huang, Mang Ye, Zekun Shi +1
Federated learning is an important privacy-preserving multi-party learning paradigm, involving collaborative learning with others and local updating on private data. Model heteroge…