Imagen de Portada

Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	He, Jun, Yu, Deying
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence Distributed, Parallel, and Cluster Computing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Safactory: A Scalable Agentic Infrastructure for Training Trustworthy Autonomous Intelligence
por: Chen, Xinquan, et al.
Publicado: (2026)

Trustworthiness of Stochastic Gradient Descent in Distributed Learning
por: Li, Hongyang, et al.
Publicado: (2024)

Galvatron: An Automatic Distributed System for Efficient Foundation Model Training
por: Liu, Xinyi, et al.
Publicado: (2025)

Efficient Resource Scheduling for Distributed Infrastructures Using Negotiation Capabilities
por: Chu, Junjie, et al.
Publicado: (2024)

Soar: Design and Deployment of A Smart Roadside Infrastructure System for Autonomous Driving
por: Shi, Shuyao, et al.
Publicado: (2024)

Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
por: Wei, Wenqi, et al.
Publicado: (2024)

Robust LLM Training Infrastructure at ByteDance
por: Wan, Borui, et al.
Publicado: (2025)

MinT: Managed Infrastructure for Training and Serving Millions of LLMs
por: Lab, Mind, et al.
Publicado: (2026)

Role-Based Fault Tolerance System for LLM RL Post-Training
por: Chen, Zhenqian, et al.
Publicado: (2025)

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
por: Hudson, Nathaniel, et al.
Publicado: (2024)

FedFiTS: Fitness-Selected, Slotted Client Scheduling for Trustworthy Federated Learning in Healthcare AI
por: Kahenga, Ferdinand, et al.
Publicado: (2025)

RollArt: Scaling Agentic RL Training via Disaggregated Infrastructure
por: Gao, Wei, et al.
Publicado: (2025)

Lightweight Trustworthy Distributed Clustering
por: Li, Hongyang, et al.
Publicado: (2025)

Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
por: Jaiswal, Shashwat, et al.
Publicado: (2025)

A Feature Engineering Approach for Business Impact-Oriented Failure Detection in Distributed Instant Payment Systems
por: Porcelli, Lorenzo
Publicado: (2025)

Laminar: A Scalable Asynchronous RL Post-Training Framework
por: Sheng, Guangming, et al.
Publicado: (2025)

A Survey of Resource-efficient LLM and Multimodal Foundation Models
por: Xu, Mengwei, et al.
Publicado: (2024)

PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training
por: Ockerman, Seth, et al.
Publicado: (2025)

From Score Distributions to Balance: Plug-and-Play Mixture-of-Experts Routing
por: Shahout, Rana, et al.
Publicado: (2025)

Redefining Data-Centric Design: A New Approach with a Domain Model and Core Data Ontology for Computational Systems
por: Johnson, William, et al.
Publicado: (2024)

Federated Learning with Blockchain-Enhanced Machine Unlearning: A Trustworthy Approach
por: Zuo, Xuhan, et al.
Publicado: (2024)

Enhancing Data Quality in Federated Fine-Tuning of Foundation Models
por: Zhao, Wanru, et al.
Publicado: (2024)

NestQuant: Post-Training Integer-Nesting Quantization for On-Device DNN
por: Xie, Jianhang, et al.
Publicado: (2025)

FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression
por: Tang, Zhenheng, et al.
Publicado: (2024)

When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
por: Zhuang, Weiming, et al.
Publicado: (2023)

DP2FL: Dual Prompt Personalized Federated Learning in Foundation Models
por: Chang, Ying, et al.
Publicado: (2025)

GPT Carry-On: Training Foundation Model for Customization Could Be Simple, Scalable and Affordable
por: Wangni, Jianqiao
Publicado: (2025)

ShadowServe: Interference-Free KV Cache Fetching for Distributed Prefix Caching
por: Xiang, Xingyu, et al.
Publicado: (2025)

From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
por: Li, Qiongxiu, et al.
Publicado: (2025)

Adaptive and Resource-efficient Agentic AI Systems for Mobile and Embedded Devices: A Survey
por: Liu, Sicong, et al.
Publicado: (2025)

UNIFERENCE: A Discrete Event Simulation Framework for Developing Distributed AI Models
por: Eldenk, Doğaç, et al.
Publicado: (2026)

AB-Training: A Communication-Efficient Approach for Distributed Low-Rank Learning
por: Coquelin, Daniel, et al.
Publicado: (2024)

COMET: A Comprehensive Cluster Design Methodology for Distributed Deep Learning Training
por: Kadiyala, Divya Kiran, et al.
Publicado: (2022)

Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey
por: Liu, Zhihong, et al.
Publicado: (2024)

Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
por: Liu, Jing, et al.
Publicado: (2025)

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices
por: Shen, Zheyu, et al.
Publicado: (2025)

On the Fragility of Data Attribution When Learning Is Distributed
por: Gao, Xian, et al.
Publicado: (2026)

Optimal Transport Aggregation for Distributed Mixture-of-Experts
por: Chamroukhi, Faïcel, et al.
Publicado: (2023)

Federated Attention: A Distributed Paradigm for Collaborative LLM Inference over Edge Networks
por: Deng, Xiumei, et al.
Publicado: (2025)

PIPO: Pipelined Offloading for Efficient Inference on Consumer Devices
por: Liu, Yangyijian, et al.
Publicado: (2025)