9 papers
Unseen Cost of Space Computing: Quantifying LEO Battery Aging via Physics-Driven Modeling
Li Zeng, Jingyang Zhu, Zixin Wang +2
Low Earth Orbit (LEO) satellite constellations in the 6G era are evolving into intelligent in-orbit computational platforms, forming Space Computing Power Networks (SCPNs) to deliv…
Service Function Chain Routing in LEO Networks Using Shortest-Path Delay Statistical Stability
Li Zeng, Zixin Wang, Yuanming Shi +1
Low Earth orbit (LEO) satellite constellations have become a critical enabler for global coverage, utilizing numerous satellites orbiting Earth at high speeds. By decomposing compl…
Pipeline Parallelism is All You Need for Optimized Early-Exit Based Self-Speculative Decoding
Ruanjun Li, Ziheng Liu, Yuanming Shi +3
Large language models (LLMs) deliver impressive generation quality, but incur very high inference cost because each output token is generated auto-regressively through all model la…
Satellite Federated Fine-Tuning for Foundation Models in Space Computing Power Networks
Yan Zhu, Jingyang Zhu, Ting Wang +3
Advancements in artificial intelligence (AI) and low-earth orbit (LEO) satellites have promoted the application of large remote sensing foundation models for various downstream tas…
Hierarchical Learning and Computing over Space-Ground Integrated Networks
Jingyang Zhu, Yuanming Shi, Yong Zhou +2
Space-ground integrated networks hold great promise for providing global connectivity, particularly in remote areas where large amounts of valuable data are generated by Internet o…
Edge Large AI Models: Collaborative Deployment and IoT Applications
Zixin Wang, Yuanming Shi, Khaled. B. Letaief
Large artificial intelligence models (LAMs) emulate human-like problem-solving capabilities across diverse domains, modalities, and tasks. By leveraging the communication and compu…