This research agenda argues that cloud-native architectures, microservices, autoscaling, and emerging trends like serverless inference and federated learning are required to make large language models efficient and scalable.
A generative caching system for large language models.arXiv preprint arXiv:2503.17603.2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda
This research agenda argues that cloud-native architectures, microservices, autoscaling, and emerging trends like serverless inference and federated learning are required to make large language models efficient and scalable.