3 papers
cs.AI2026
Rollout Cards: A Reproducibility Standard for Agent Research
Charlie Masters, Ziyuan Liu, Stefano V. Albrecht
Reproducibility problems that have long affected machine learning and reinforcement learning are now surfacing in agent research: papers compare systems by reported scores while le…
cs.AI2025
ARCANE: A Multi-Agent Framework for Interpretable and Configurable Alignment
Charlie Masters, Marta GrzeÅkiewicz, Stefano V. Albrecht
As agents based on large language models are increasingly deployed to long-horizon tasks, maintaining their alignment with stakeholder preferences becomes critical. Effective align…
cs.AI2025
Towards Ethical Multi-Agent Systems of Large Language Models: A Mechanistic Interpretability Perspective
Jae Hee Lee, Anne Lauscher, Stefano V. Albrecht
Large language models (LLMs) have been widely deployed in various applications, often functioning as autonomous agents that interact with each other in multi-agent systems. While t…