6 papers · 1 filter
Too much evidence, too little time: From text to actionable recommendations through multi-objective evidence reasoning
Adela Bara, Simona-Vasilica Oprea
Evidence-based clinical decision making requires specialists to identify, evaluate and synthesize relevant scientific literature. However, PubMed searches for complex clinical case…
CHAINTRIX: A multi-pipeline LLM-augmented framework for automated smart-contract security auditing
Gabriela Dobrita, Simona-Vasilica Oprea, Adela Bara
Smart-contract exploits have caused billions of USD in cumulative losses, yet audits remain expensive and slow. Automated tools have emerged to close this gap, but each class has a…
Think it, Run it: Autonomous ML pipeline generation via self-healing multi-agent AI
Adela Bara, Gabriela Dobrita, Simona-Vasilica Oprea
The purpose of our paper is to develop a unified multi-agent architecture that automates end-to-end machine learning (ML) pipeline generation from datasets and natural-language (NL…
A phenotype-driven and evidence-governed framework for knowledge graph enrichment and hypotheses discovery in population data
Adela Bâra, Simona-Vasilica Oprea
Current knowledge graph (KG) construction methods are confirmatory, focusing on recovering known relationships rather than identifying novel or context-dependent nodes. This paper…
Are we still able to recognize pearls? Machine-driven peer review and the risk to creativity: An explainable RAG-XAI detection framework with markers extraction
Alin-Gabriel VÄduva, Simona-Vasilica Oprea, Adela Bâra
The integration of large language models (LLMs) into peer review raises a concern beyond authorship and detection: the potential cascading automation of the entire editorial proces…
Measuring the Fragility of Trust: Devising Credibility Index via Explanation Stability (CIES) for Business Decision Support Systems
Alin-Gabriel Vaduva, Simona-Vasilica Oprea, Adela Bara
Explainable Artificial Intelligence (XAI) methods (SHAP, LIME) are increasingly adopted to interpret models in high-stakes businesses. However, the credibility of these explanation…