4 papers
Faster Verified Explanations for Neural Networks
Alessandro De Palma, Greta Dolcetti, Caterina Urban
Verified explanations are a principled way to explain the decisions taken by neural networks, which are otherwise black-box in nature. However, these techniques face significant sc…
Blue Teaming Function-Calling Agents
Greta Dolcetti, Giulio Zizzo, Sergio Maffeis
We present an experimental evaluation that assesses the robustness of four open source LLMs claiming function-calling capabilities against three different attacks, and we measure t…
Building a Foundational Guardrail for General Agentic Systems via Synthetic Data
Yue Huang, Hang Hua, Yujun Zhou +11
While LLM agents can plan multi-step tasks, intervening at the planning stage-before any action is executed-is often the safest way to prevent harm, since certain risks can lead to…
Helping LLMs Improve Code Generation Using Feedback from Testing and Static Analysis
Greta Dolcetti, Vincenzo Arceri, Eleonora Iotti +3
Large Language Models (LLMs) are one of the most promising developments in the field of artificial intelligence, and the software engineering community has readily noticed their po…