22 citations · 22 across the 5 of their papers we have counts for
5 papers
Unaccountable Delegation, Fading Skills: Mapping the Risks of Workplace AI Agents
Gabriele La Malfa, Lakmal Meegahapola, Edyta Bogucka +4
To anticipate socio-technical risks from AI agents, organizations need taxonomies to classify them. However, existing AI risk taxonomies focus on broad risks and do not capture job…
The Attacker in the Mirror: Breaking Self-Consistency in Safety via Anchored Bipolicy Self-Play
Gabriele La Malfa, Emanuele La Malfa, Saar Cohen +4
Self-play red team is an established approach to improving AI safety in which different instances of the same model play attacker and defender roles in a zero-sum game, i.e., where…
Fairness Aware Reinforcement Learning via Proximal Policy Optimization
Gabriele La Malfa, Jie M. Zhang, Michael Luck +1
Fairness in multi-agent systems (MAS) focuses on equitable reward distribution among agents in scenarios involving sensitive attributes such as race, gender, or socioeconomic statu…
Using Protected Attributes to Consider Fairness in Multi-Agent Systems
Gabriele La Malfa, Jie M. Zhang, Michael Luck +1
Fairness in Multi-Agent Systems (MAS) has been extensively studied, particularly in reward distribution among agents in scenarios such as goods allocation, resource division, lotte…
AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation
Dong Huang, Jie M. Zhang, Michael Luck +3
The advancement of natural language processing (NLP) has been significantly boosted by the development of transformer-based large language models (LLMs). These models have revoluti…