8 papers
Hallucination Mitigation with Agentic AI, Nested Learning, and AI Sustainability via Semantic Caching
Diego Gosmar, Deborah A. Dahl
This paper describes an approach to hallucination detection and mitigation using a HOPE-inspired Nested Learning architecture with Continuum Memory Systems (CMS) and semantic simil…
MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop
Diego Gosmar, Giovanni Zenezini
Document processing automation remains a critical challenge in enterprise environments, where traditional manual approaches are labor-intensive and error-prone. We present MADP, a…
Prompt Injection Mitigation with Agentic AI, Nested Learning, and AI Sustainability via Semantic Caching
Diego Gosmar, Deborah A. Dahl
Prompt injection remains a central obstacle to the safe deployment of large language models, particularly in multi-agent settings where intermediate outputs can propagate or amplif…
Agentic AI Sustainability Assessment for Supply Chain Document Insights
Diego Gosmar, Anna Chiara Pallotta, Giovanni Zenezini
This paper presents a comprehensive sustainability assessment framework for document intelligence within supply chain operations, centered on agentic artificial intelligence (AI).…
Sentinel Agents for Secure and Trustworthy Agentic AI in Multi-Agent Systems
Diego Gosmar, Deborah A. Dahl
This paper proposes a novel architectural framework aimed at enhancing security and reliability in multi-agent systems (MAS). A central component of this framework is a network of…
Prompt Injection Detection and Mitigation via AI Multi-Agent NLP Frameworks
Diego Gosmar, Deborah A. Dahl, Dario Gosmar
Prompt injection constitutes a significant challenge for generative AI systems by inducing unintended outputs. We introduce a multi-agent NLP framework specifically designed to add…