Cover Image

ARYA: A Physics-Constrained Composable & Deterministic World Model Architecture

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dobrin, Seth, Chmiel, Lukasz
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP
by: Zhang, Jinyu, et al.
Published: (2026)

The Case for Co-Designing Model Architectures with Hardware
by: Anthony, Quentin, et al.
Published: (2024)

Transformer-Based Model for Cold Start Mitigation in FaaS Architecture
by: Mouen, Alexandre Savi Fayam Mbala, et al.
Published: (2025)

Federated Fine-Tuning of Sparsely-Activated Large Language Models on Resource-Constrained Devices
by: Chen, Fahao, et al.
Published: (2025)

AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework
by: Luo, Xubin, et al.
Published: (2026)

A Secure and Trustworthy Network Architecture for Federated Learning Healthcare Applications
by: Boiano, Antonio, et al.
Published: (2024)

Beluga: A CXL-Based Memory Architecture for Scalable and Efficient LLM KVCache Management
by: Yang, Xinjun, et al.
Published: (2025)

LLM as HPC Expert: Extending RAG Architecture for HPC Data
by: Miyashita, Yusuke, et al.
Published: (2024)

Scalable Cloud-Native Architectures for Intelligent PMU Data Processing
by: Chockalingam, Nachiappan, et al.
Published: (2025)

B-PASTE: Beam-Aware Pattern-Guided Speculative Execution for Resource-Constrained LLM Agents
by: Song, Yanfei
Published: (2026)

Safe and Compliant Cross-Market Trade Execution via Constrained RL and Zero-Knowledge Audits
by: Borjigin, Ailiya, et al.
Published: (2025)

Scalable Runtime Architecture for Data-driven, Hybrid HPC and ML Workflow Applications
by: Merzky, Andre, et al.
Published: (2025)

Privacy-Preserving Federated Learning: Integrating Zero-Knowledge Proofs in Scalable Distributed Architectures
by: Gupta, Divya
Published: (2026)

Watt Counts: Energy-Aware Benchmark for Sustainable LLM Inference on Heterogeneous GPU Architectures
by: Argerich, Mauricio Fadel, et al.
Published: (2026)

High-Dimensional Data Processing: Benchmarking Machine Learning and Deep Learning Architectures in Local and Distributed Environments
by: Rodriguez, Julian, et al.
Published: (2025)

Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures
by: Georganas, Evangelos, et al.
Published: (2023)

Cyber Physical Games
by: Sritriratanarak, Warisa, et al.
Published: (2024)

DataCenterGym: A Physics-Grounded Simulator for Multi-Objective Data Center Scheduling
by: Pathak, Nilavra, et al.
Published: (2026)

Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure
by: He, Jun, et al.
Published: (2026)

Transforming Future Data Center Operations and Management via Physical AI
by: Cao, Zhiwei, et al.
Published: (2025)

Deploying Foundation Model Powered Agent Services: A Survey
by: Xu, Wenchao, et al.
Published: (2024)

A Hashgraph-Inspired Consensus Mechanism for Reliable Multi-Model Reasoning
by: Ogunsina, Kolawole E., et al.
Published: (2025)

A Model Aware AIGC Task Offloading Algorithm in IIoT Edge Computing
by: Wang, Xin, et al.
Published: (2025)

HETHUB: A Distributed Training System with Heterogeneous Cluster for Large-Scale Models
by: Xu, Si, et al.
Published: (2024)

A Survey on Large Language Model Acceleration based on KV Cache Management
by: Li, Haoyang, et al.
Published: (2024)

Efficient Multi-Model Orchestration for Self-Hosted Large Language Models
by: Vangala, Bhanu Prakash, et al.
Published: (2025)

HPC-Coder: Modeling Parallel Programs using Large Language Models
by: Nichols, Daniel, et al.
Published: (2023)

Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference
by: Huang, Yafan, et al.
Published: (2026)

EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models
by: Cheng, Jialiang, et al.
Published: (2024)

Training Overhead Ratio: A Practical Reliability Metric for Large Language Model Training Systems
by: Lu, Ning, et al.
Published: (2024)

PlanetServe: A Decentralized, Scalable, and Privacy-Preserving Overlay for Democratizing Large Language Model Serving
by: Fang, Fei, et al.
Published: (2025)

CCL-D: A High-Precision Diagnostic System for Slow and Hang Anomalies in Large-Scale Model Training
by: Gu, Yida, et al.
Published: (2026)

Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE
by: Firoz, Jesun, et al.
Published: (2025)

Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
by: Yang, Haowei, et al.
Published: (2025)

Boosting Asynchronous Decentralized Learning with Model Fragmentation
by: Biswas, Sayan, et al.
Published: (2024)

Demystifying the Communication Characteristics for Distributed Transformer Models
by: Anthony, Quentin, et al.
Published: (2024)

Scaling Performance of Large Language Model Pretraining
by: Interrante-Grant, Alexander, et al.
Published: (2025)

Domain-Adaptive Model Merging Across Disconnected Modes
by: Liu, Junming, et al.
Published: (2026)

Can Large Language Models Write Parallel Code?
by: Nichols, Daniel, et al.
Published: (2024)

Hierarchical Autoscaling for Large Language Model Serving with Chiron
by: Patke, Archit, et al.
Published: (2025)