3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2025
The M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments
Srikanth Thudumu, Hy Nguyen, Hung Du +6
Neural Architecture Search (NAS) aims to automate the design of deep neural networks. However, existing NAS techniques often focus on maximising accuracy, neglecting model efficien…
cs.CL2024★ 3 cited
RAGProbe: An Automated Approach for Evaluating RAG Applications
Shangeetha Sivasothy, Scott Barnett, Stefanus Kurniawan +2
Retrieval Augmented Generation (RAG) is increasingly being used when building Generative AI applications. Evaluating these applications and RAG pipelines is mostly done manually, v…