Explore Our Latest Research Papers

Security Degradation in Iterative AI Code Generation: A Systematic Analysis of the Paradox

Approaches to Responsible Governance of GenAI in Organizations

Transparent AI - The case for Interpretability and Explainability

A Stochastic Differential Equation Framework for Multi-Objective LLM Interactions: Dynamical Systems Analysis with Code Generation Applications

Security Knowledge Dilution in Large Language Models: How Irrelevant Context Degrades Critical Domain Expertise

Security Charter Effectiveness in Large Language Model Code Generation: A Multi-Phase Experimental Analysis Revealing Task-Dependent Responsiveness and Architectural Differences

Temporal Privacy Drift in Tool-Augmented Large Language Models: A Quantitative Framework for Language Models Big Data System Security

Proof-Carrying Answers: A Systematic Protocol for Verifiable Retrieval-Augmented Generation with Cryptographic Provenance

AI Governance Workshop: Alignment, Morality, Law, and Design (AIGOV)

AI CONNECTORS: Domain Experts as Collaborative Orchestrators for Safe and Aligned Agentic AI Governance

Joint Evaluation : A Human + LLM + Multi-Agents Collaborative Framework for Comprehensive AI Safety (Jo.E)

Governance- and Security-by-Design: Embedding Safety and Alignment into Agentic AI Systems

Joint Evaluation (Jo.E): A Collaborative Framework for Rigorous Safety and Alignment Evaluation of AI Systems Integrating Human Expertise, LLMs, and AI Agents

AI Governance by Design for Agentic Systems: A Framework for Responsible Development and Deployment