32 citations · 85 across the 16 of their papers we have counts for
10 papers · 1 filter
PhoneLM:an Efficient and Capable Small Language Model Family through Principled Pre-training
Rongjie Yi, Xiang Li, Weikai Xie +6
The interest in developing small language models (SLM) for on-device deployment is fast growing. However, the existing SLM design hardly considers the device hardware characteristi…
Recall: Empowering Multimodal Embedding for Edge Devices
Dongqi Cai, Shangguang Wang, Chen Peng +2
Human memory is inherently prone to forgetting. To address this, multimodal embedding models have been introduced, which transform diverse real-world data into a unified embedding…
Small Language Models: Survey, Measurements, and Insights
Zhenyan Lu, Xiang Li, Dongqi Cai +5
Small language models (SLMs), despite their widespread adoption in modern smart devices, have received significantly less academic attention compared to their large language model…
FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Experts
Hanzi Mei, Dongqi Cai, Ao Zhou +2
As Large Language Models (LLMs) push the boundaries of AI capabilities, their demand for data is growing. Much of this data is private and distributed across edge devices, making F…
The CAP Principle for LLM Serving: A Survey of Long-Context Large Language Model Serving
Pai Zeng, Zhenyu Ning, Jieru Zhao +5
We survey the large language model (LLM) serving area to understand the intricate dynamics between cost-efficiency and accuracy, which is magnified by the growing need for longer c…
FedRDMA: Communication-Efficient Cross-Silo Federated LLM via Chunked RDMA Transmission
Zeling Zhang, Dongqi Cai, Yiran Zhang +3
Communication overhead is a significant bottleneck in federated learning (FL), which has been exaggerated with the increasing size of AI models. In this paper, we propose FedRDMA,…
Resource-efficient In-orbit Detection of Earth Objects
Qiyang Zhang, Xin Yuan, Ruolin Xing +6
With the rapid proliferation of large Low Earth Orbit (LEO) satellite constellations, a huge amount of in-orbit data is generated and needs to be transmitted to the ground for proc…
A Survey of Resource-efficient LLM and Multimodal Foundation Models
Mengwei Xu, Wangsong Yin, Dongqi Cai +15
Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine lear…
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li, Hao Wen, Weijun Wang +22
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming…
Deciphering the Enigma of Satellite Computing with COTS Devices: Measurement and Analysis
Ruolin Xing, Mengwei Xu, Ao Zhou +4
In the wake of the rapid deployment of large-scale low-Earth orbit satellite constellations, exploiting the full computing potential of Commercial Off-The-Shelf (COTS) devices in t…