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Nonlinear topological edge states, topological gap solitons, and self-induced topological edge states in nonlinear Su-Schrieffer-Heeger circuit lattices
arXiv:2504.11964v3 Announce Type: replace Abstract: Topological edge states typically arise at the boundaries of topologically nontrivial structures or at interfaces between regions with different topological invariants. When topological systems are extended into the nonlinear regime, linear topological edge states bifurcate into nonlinear counterparts, and topological gap solitons emerge in the bulk of the structures. Extensive studies of nonlinear topological edge states and topological...
High-energy topological edge states and strain-induced multiple flat bands in a honeycomb lattice
arXiv:2605.31182v1 Announce Type: new Abstract: We propose a novel anti-twig edge in the honeycomb lattice (HCL) that supports two symmetric high-energy edge states. It is different from the twig edge supporting the zero-energy flat band. Moreover, multiple flat bands are produced by applying a strain to the HCL with a twig edge or an anti-twig edge, and the suppression or enhancement of the high-energy edge state is observed.
SIGMA: A Versatile Streaming Graph Partitioner for Vertex- and Edge-Balanced Distributed GNN Training
Announce Type: new Abstract: Distributed Graph Neural Network (GNN) training depends critically on how the underlying graph is partitioned across compute resources. Existing graph partitioners focus either on vertex partitioning or edge partitioning and typically optimize only a single communication objective (edge cut or vertex cut) under a single balance constraint (vertex balance or edge balance).
CANS: Accelerating Multiuser Collaborative Edge Inference via Cooperative Autodidactic NeuroSurgeon
Announce Type: new Abstract: Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering intelligent services to resource-constrained mobile devices. A representative scenario is multi-user collaborative edge inference, where distinct devices independently partition their DNN models and offload backend computation to a common edge server over wireless networks. However, determining the optimal DNN...
Real-World Deployment of a 5G-Connected Edge-Controlled Aerial Robot in Industrial Subterranean Mines
arXiv:2606.04818v1 Announce Type: new Abstract: This article presents the first real-world autonomous flight of a 5G-connected aerial robot controlled by an edge-offloaded controller, and aims to bridge the gap between controlled and factual setups. The robot operates within an active industrial subterranean mine, while the high-level controller is deployed in a nearby Kubernetes-based edge cluster. Communication between the robot and the edge is enabled via a 5G New Radio (NR) Standalone...
Compact LLM Deployment and World Model Assisted Offloading in Mobile Edge Computing
Announce Type: replace Abstract: This paper investigates compact large language model (LLM) deployment and world-model-assisted inference offloading in mobile edge computing (MEC) networks. We first propose an edge compact LLM deployment (ECLD) framework that jointly applies structured pruning, low-bit quantization, and knowledge distillation to construct edge-deployable LLM variants, and we evaluate these models using four complementary metrics: accessibility, energy consumption,...
Machine learning uncovers 1,750 quakes tracing 250-kilometer edge of Alaska microplate
Machine learning uncovers 1,750 quakes tracing 250-kilometer edge of Alaska microplate Andrew Zinin Lead Editor Thousands of small earthquakes, detected for the first time by a machine-learning process, reveal the distinct, razor-sharp edge of the Yakutat microplate as it subducts beneath the North American plate. The Yakutat oceanic plateau is caught in the middle of a tectonic traffic jam with the Pacific plate as it subducts beneath the North American plate. The position and structure of...
STEPS: Semantic-Contract-Guided Scheduling for LLM-Assisted Natural-Language-Driven Edge AI Services
arXiv:2606.09537v1 Announce Type: new Abstract: Networked AI services are increasingly delivered through edge infrastructures to support latency-sensitive applications. Edge scheduling is critical for deciding where and how AI services are executed under limited communication and computing resources. Existing frameworks usually assume that requirements are given as numerical constraints, such as latency bounds, energy budgets, or cost limits.
Motorola announces the $600 Edge 2026 phone
Motorola announces the $600 Edge 2026 phone The company has also unveiled the $100 Moto Buds 2. Motorola has unveiled a new mid-range phone, the Motorola Edge 2026, which you'll be able to get for $600.
Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System
Announce Type: replace Abstract: Federated Learning (FL) is an emerging distributed machine learning (ML) technique that enables in-situ model training and inference on decentralized edge devices. We propose Totoro$^+$, a novel scalable FL system that enables massive FL applications to run simultaneously on edge networks. The key insight is to explore a distributed hash table (DHT)-based peer-to-peer (P2P) model to re-architect the centralized FL system design into a fully decentralized one.