14 citations · 28 across the 9 of their papers we have counts for
11 papers
Resuming Vision-Language Inference across Onboard Interruptions
Xiaolong Huang, Yinyuan Zhang, Daliang Xu +6
Executing vision-language models (VLMs) aboard low-Earth orbit satellites enables flexible processing of observation data without first downlinking it to the ground. On commercial…
Resource-Aware Parameter-Efficient Model Adaptation for Onboard High-Dimensional Data
Qiyang Zhang, Xinhao Li, Lei Shi +4
Onboard satellite models often require frequent updates, but the weights adapted to earlier data distributions can quickly become outdated. However, updating large-scale model para…
Characterizing the Landscape of Open-Source Satellite Software
Jinfeng Wen, Qi Liang, Yuehan Sun +4
Satellites have become fundamental components of modern technological systems, supporting critical infrastructure in communication, navigation, Earth observation, and scientific re…
AI Infrastructure in Space: How Far Can We Go?
Qing Li, Qiyang Zhang, Daliang Xu +10
Satellites are becoming programmable computing platforms capable of running increasingly demanding AI workloads. This shift raises a systems problem: how can AI services remain dep…
SateLight: A Satellite Application Update Framework for Satellite Computing
Jinfeng Wen, Jianshu Zhao, Zixi Zhu +4
Satellite computing is an emerging paradigm that empowers satellites to perform onboard processing tasks (i.e., \textit{satellite applications}), thereby reducing reliance on groun…
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…
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature Compression
Alireza Furutanpey, Qiyang Zhang, Philipp Raith +3
Nanosatellite constellations equipped with sensors capturing large geographic regions provide unprecedented opportunities for Earth observation. As constellation sizes increase, ne…
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…
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…
The First Verification Test of Space-Ground Collaborative Intelligence via Cloud-Native Satellites
Shangguang Wang, Qiyang Zhang, Ruolin Xing +2
Recent advancements in satellite technologies and the declining cost of access to space have led to the emergence of large satellite constellations in Low Earth Orbit. However, the…
Collaborative Inference in DNN-based Satellite Systems with Dynamic Task Streams
Jinglong Guan, Qiyang Zhang, Ilir Murturi +3
As a driving force in the advancement of intelligent in-orbit applications, DNN models have been gradually integrated into satellites, producing daily latency-constraint and comput…