115 citations · 346 across the 42 of their papers we have counts for
47 papers
Cloud, Edge, or Split? Profiling Onboard and Split Vision-Language Model Deployment for Drone AI
Zoha Azimi, Reza Farahani, Schahram Dustdar +1
Vision-Language Models (VLMs) enable edge devices like unmanned aerial vehicles (UAVs) to interpret visual observations and reason about complex environments using natural-language…
PyStream: Enhancing Video Streaming Evaluation
Samuel Radler, Leon Prüller, Emanuele Artioli +2
As streaming services become more commonplace, analyzing their behavior effectively under different network conditions is crucial. This is normally quite expensive, requiring multi…
Perceptual Refinement of an End-to-End Video Streaming Pipeline via Generative AI Layers
Emanuele Artioli, Farzad Tashtarian, Christian Timmerer
Traditional codecs treat every region of a frame alike; a generative layer can instead degrade the regions a viewer attends to least and reconstruct them at the client. We present…
DRLM: Deep Reinforcement Learning-Based LLM Query Orchestration in Edge Environments
Reza Farahani, Zoha Azimi Ourimi, Mario Colosi +3
Large language model (LLM) services increasingly process heterogeneous queries with diverse latency, accuracy, and resource requirements. While edge deployment reduces response tim…
Thin-Client Interactive Gaussian Adaptive Streaming over HTTP/3
Emanuele Artioli, Philipp Fößl, Daniele Lorenzi +4
Recent advancements in 3D Gaussian Splatting (3DGS) have enabled photorealistic rendering of complex scenes, yet widespread adoption on mobile and Extended Reality (XR) devices is…
DQ-Ladder: A Deep Reinforcement Learning-based Bitrate Ladder for Adaptive Video Streaming
Reza Farahani, Zoha Azimi, Vignesh V Menon +4
Adaptive streaming of segmented video over HTTP typically relies on a predefined set of bitrate-resolution pairs, known as a bitrate ladder. However, fixed ladders often overlook v…