arXiv AI
EV-JEPA: Elastic V-JEPA for Any Device and Cross-Device Inference
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Stepped MoE: Segment-Level Routing with Configurable Inference Complexity
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Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation
arXiv:2609.10018v1 Announce Type: new Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these de...
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Adaptive AI Task Partitioning and Safe Offloading in Heterogeneous Edge-Cloud Continuum
The paper introduces a dynamic framework for partitioning neural network layers across a heterogeneous edge‑cloud continuum, adapting to runtime changes in network conditions and device capabilities. It profiles models at startup, measures link quality, and periodically re‑evaluates the partitioning to optimize performance. Experiments on a Raspberry Pi, laptop, and desktop using VGG16, AlexNet, and MobileNetV2 demonstrate energy savings of 27.09–35.82% and latency reductions of 6.34–22.92% over static partitioning.
arXiv AI
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DySCo: Dynamic Sharding for Collaborative Edge-Cloud LLM Inference with Depth-Synchronized Batching
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arXiv Machine Learning
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HydraLLM: Adaptive Width Slicing for Elastic Text and Vision-Language Models
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arXiv AI
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E2LLM: Towards Efficient LLM Serving in Heterogeneous Edge/Fog Environments
arXiv:2606. 03770v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become integral to modern applications, yet their deployment remains challenging.