Think it, Run it: Autonomous ML pipeline generation via self-healing multi-agent AI

This paper proposes a unified multi-agent AI architecture to automate end-to-end machine learning (ML) pipeline generation from datasets and natural-language goals. The five-agent system integrates RAG, an explainable hybrid recommender, and an LLM-based self-healing mechanism, achieving an 84.7% success rate and improved robustness.