5 citations · 6 across the 9 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…