5 citations · 10 across the 5 of their papers we have counts for
6 papers
WayFinder: Hierarchical Visual-Language-Action for Zero-Shot Waypoint Generation and Low-Level Kinematic Control
Timothy K Johnsen, Marco Levorato
Visual Language Action (VLA) models offer unprecedented generalization for autonomous robots; however, their real-world deployment is frequently bottlenecked by unreliable executio…
A Multi-task Supervised Compression Model for Split Computing
Yoshitomo Matsubara, Matteo Mendula, Marco Levorato
Split computing ( split learning) is a promising approach to deep learning models for resource-constrained edge computing systems, where weak sensor (mobile) devices are wire…
Improving Multi-candidate Speculative Decoding
Xiaofan Lu, Yixiao Zeng, Feiyang Ma +2
Speculative Decoding (SD) is a technique to accelerate the inference of Large Language Models (LLMs) by using a lower complexity draft model to propose candidate tokens verified by…
NaviSlim: Adaptive Context-Aware Navigation and Sensing via Dynamic Slimmable Networks
Tim Johnsen, Marco Levorato
Small-scale autonomous airborne vehicles, such as micro-drones, are expected to be a central component of a broad spectrum of applications ranging from exploration to surveillance…
NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation
Timothy K Johnsen, Ian Harshbarger, Zixia Xia +1
Lightweight autonomous unmanned aerial vehicles (UAV) are emerging as a central component of a broad range of applications. However, autonomous navigation necessitates the implemen…
SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing
Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato +1
Modern IEEE 802.11 (Wi-Fi) networks extensively rely on multiple-input multiple-output (MIMO) to significantly improve throughput. To correctly beamform MIMO transmissions, the acc…