1 citations · 2 across the 5 of their papers we have counts for
6 papers
Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
Senyao Li, Haozhao Wang, Wenchao Xu +6
As large language models (LLMs) evolve, deploying them solely in the cloud or compressing them for edge devices has become inadequate due to concerns about latency, privacy, cost,…
Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey
Yichen Li, Haozhao Wang, Wenchao Xu +9
Non-Centralized Continual Learning (NCCL) has become an emerging paradigm for enabling distributed devices such as vehicles and servers to handle streaming data from a joint non-st…
Detached and Interactive Multimodal Learning
Yunfeng Fan, Wenchao Xu, Haozhao Wang +2
Recently, Multimodal Learning (MML) has gained significant interest as it compensates for single-modality limitations through comprehensive complementary information within multimo…
OTAS: An Elastic Transformer Serving System via Token Adaptation
Jinyu Chen, Wenchao Xu, Zicong Hong +4
Transformer model empowered architectures have become a pillar of cloud services that keeps reshaping our society. However, the dynamic query loads and heterogeneous user requireme…
Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection
Yunfeng Fan, Wenchao Xu, Haozhao Wang +3
Selecting proper clients to participate in each federated learning (FL) round is critical to effectively harness a broad range of distributed data. Existing client selection method…
Balanced Multi-modal Federated Learning via Cross-Modal Infiltration
Yunfeng Fan, Wenchao Xu, Haozhao Wang +2
Federated learning (FL) underpins advancements in privacy-preserving distributed computing by collaboratively training neural networks without exposing clients' raw data. Current F…