2 citations · 3 across the 5 of their papers we have counts for
5 papers
End-to-End Data Quality-Driven Framework for Machine Learning in Production Environment
Firas Bayram, Bestoun S. Ahmed, Erik Hallin
This paper introduces a novel end-to-end framework that efficiently integrates data quality assessment with machine learning (ML) model operations in real-time production environme…
Quality Assurance for LLM-RAG Systems: Empirical Insights from Tourism Application Testing
Bestoun S. Ahmed, Ludwig Otto Baader, Firas Bayram +2
This paper presents a comprehensive framework for testing and evaluating quality characteristics of Large Language Model (LLM) systems enhanced with Retrieval-Augmented Generation…
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
Firas Bayram, Bestoun S. Ahmed
Artificial intelligence (AI), and especially its sub-field of Machine Learning (ML), are impacting the daily lives of everyone with their ubiquitous applications. In recent years,…
Adaptive Data Quality Scoring Operations Framework using Drift-Aware Mechanism for Industrial Applications
Firas Bayram, Bestoun S. Ahmed, Erik Hallin
Within data-driven artificial intelligence (AI) systems for industrial applications, ensuring the reliability of the incoming data streams is an integral part of trustworthy decisi…
From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors
Firas Bayram, Bestoun S. Ahmed, Andreas Kassler
The dynamicity of real-world systems poses a significant challenge to deployed predictive machine learning (ML) models. Changes in the system on which the ML model has been trained…