2 citations · 7 across the 12 of their papers we have counts for
6 papers · 1 filter
Traceability and Accountability in Role-Specialized Multi-Agent LLM Pipelines
Amine Barrak
Sequential multi-agent systems built with large language models (LLMs) can automate complex software tasks, but they are hard to trust because errors quietly pass from one stage to…
Cost-Performance Analysis: A Comparative Study of CPU-Based Serverless and GPU-Based Training Architectures
Amine Barrak, Fabio Petrillo, Fehmi Jaafar
The field of distributed machine learning (ML) faces increasing demands for scalable and cost-effective training solutions, particularly in the context of large, complex models. Se…
CARGO: A Framework for Confidence-Aware Routing of Large Language Models
Amine Barrak, Yosr Fourati, Michael Olchawa +2
As large language models (LLMs) proliferate in scale, specialization, and latency profiles, the challenge of routing user prompts to the most appropriate model has become increasin…
FaaSGuard: Secure CI/CD for Serverless Applications -- An OpenFaaS Case Study
Amine Barrak, Emna Ksontini, Ridouane Atike +1
Serverless computing significantly alters software development by abstracting infrastructure management and enabling rapid, modular, event-driven deployments. Despite its benefits,…
From REST to MCP: An Empirical Study of API Wrapping and Automated Server Generation for LLM Agents
Meriem Mastouri, Emna Ksontini, Amine Barrak +1
The Model Context Protocol (MCP) is emerging as a standard interface through which LLM agents invoke external tools, and a growing ecosystem of MCP servers now mediates access to v…
Scalable and Cost-Efficient ML Inference: Parallel Batch Processing with Serverless Functions
Amine Barrak, Emna Ksontini
As data-intensive applications grow, batch processing in limited-resource environments faces scalability and resource management challenges. Serverless computing offers a flexible…