1 citations · 2 across the 6 of their papers we have counts for
6 papers
EdgeMLBalancer: A Self-Adaptive Approach for Dynamic Model Switching on Resource-Constrained Edge Devices
Akhila Matathammal, Kriti Gupta, Larissa Lavanya +3
The widespread adoption of machine learning on edge devices, such as mobile phones, laptops, IoT devices, etc., has enabled real-time AI applications in resource-constrained enviro…
LLMs for Generation of Architectural Components: An Exploratory Empirical Study in the Serverless World
Shrikara Arun, Meghana Tedla, Karthik Vaidhyanathan
Recently, the exponential growth in capability and pervasiveness of Large Language Models (LLMs) has led to significant work done in the field of code generation. However, this gen…
Leveraging LLMs for Dynamic IoT Systems Generation through Mixed-Initiative Interaction
Bassam Adnan, Sathvika Miryala, Aneesh Sambu +3
IoT systems face significant challenges in adapting to user needs, which are often under-specified and evolve with changing environmental contexts. To address these complexities, u…
Approach Towards Semi-Automated Certification for Low Criticality ML-Enabled Airborne Applications
Chandrasekar Sridhar, Vyakhya Gupta, Prakhar Jain +1
As Machine Learning (ML) makes its way into aviation, ML enabled systems including low criticality systems require a reliable certification process to ensure safety and performance…
LoCoML: A Framework for Real-World ML Inference Pipelines
Kritin Maddireddy, Santhosh Kotekal Methukula, Chandrasekar Sridhar +1
The widespread adoption of machine learning (ML) has brought forth diverse models with varying architectures, and data requirements, introducing new challenges in integrating these…
Engineering LLM Powered Multi-agent Framework for Autonomous CloudOps
Kannan Parthasarathy, Karthik Vaidhyanathan, Rudra Dhar +8
Cloud Operations (CloudOps) is a rapidly growing field focused on the automated management and optimization of cloud infrastructure which is essential for organizations navigating…