Systems & Networks · Computer Science & AI
Distributed & Parallel Computing
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507 papers, from 4 September 2026 to 5 November 2026: 507 arXiv preprints.
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Newest papers, page 26
Don't Be Afraid to Die: Black Hole Search in Dynamic Graphs with Fewer Agents
We consider a team of synchronous mobile agents operating in a port-labeled network.Polynomial Lower Bounds for Distributed Graph Sketching with Tiny Error: Connectivity and Spanning Tree Construction
We present the first polynomial lower bounds for several fundamental problems in the distributed graph sketching model in the tiny-error regime, which includes deterministic algorithms as a special…CALM: Class-wise Agreement and Label-gated Disagreement Modulation for Decentralized Federated Learning
Conventional federated learning relies on parameter averaging, which forces clients to be doubly homogeneous: all must run an identical architecture, and accuracy degrades when local data are non-IID.FANS: Federated Adaptive Network Search Learning for Heterogeneous Devices
Heterogeneous Federated Learning (HFL) aims to train models across devices with diverse resource budgets while preserving data privacy.Diamond Agent: Agentic Control of Federated HPC Resources as a Service
Efficiently aggregating and orchestrating computing power across heterogeneous clusters for HPC workflows faces four practical challenges: preserving workflow context across independently…Solution-space heterogeneity shapes federated learning dynamics across partial differential equations
Federated scientific machine learning enables institutions to train neural surrogates without centralizing local physical data, yet studies of partial differential equations (PDEs) lack a…From 80x to 385x: A Best-Matching-Unit Search at the L2 Roof, Measured Against a Symmetrically Tuned Baseline
Comparisons between GPU implementations are usually asymmetric: one side is tuned by its author, the other is run as found.