works on

From the 1 of 11 linked papers with an AI index.

activity
20242026
collaborators

11 papers

cs.CL2026

Step-Tagging: Toward controlling the generation of Language Reasoning Models through step monitoring

Yannis Belkhiter, Seshu Tirupathi, Giulio Zizzo +1

The paper proposes Step-Tagging, a lightweight classifier that tags reasoning steps generated by language reasoning models in real time, enabling monitoring and early stopping to r…

cs.CL2026

TRACES: Tagging Reasoning Steps for Adaptive Cost-Efficient Early-Stopping

Yannis Belkhiter, Seshu Tirupathi, Giulio Zizzo +1

The field of Language Reasoning Models (LRMs) has been very active over the past few years with advances in training and inference techniques enabling LRMs to reason longer, and mo…

cs.CR2026

Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models

Yannis Belkhiter, Giulio Zizzo, Sergio Maffeis +2

The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the capabilities of AI-powered system by inv…

cs.CR2026

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…

cs.LG2025

Dynamic Features Adaptation in Networking: Toward Flexible training and Explainable inference

Yannis Belkhiter, Seshu Tirupathi, Giulio Zizzo +2

As AI becomes a native component of 6G network control, AI models must adapt to continuously changing conditions, including the introduction of new features and measurements driven…

cs.LG2025

Pre-Hoc Predictions in AutoML: Leveraging LLMs to Enhance Model Selection and Benchmarking for Tabular datasets

Yannis Belkhiter, Seshu Tirupathi, Giulio Zizzo +2

The field of AutoML has made remarkable progress in post-hoc model selection, with libraries capable of automatically identifying the most performing models for a given dataset. Ne…