3 citations · 4 across the 6 of their papers we have counts for
6 papers
Multilingual Self-Taught Faithfulness Evaluators
Carlo Alfano, Aymen Al Marjani, Zeno Jonke +3
The growing use of large language models (LLMs) has increased the need for automatic evaluation systems, particularly to address the challenge of information hallucination. Althoug…
Meta-Learning Objectives for Preference Optimization
Carlo Alfano, Silvia Sapora, Jakob Nicolaus Foerster +2
Evaluating preference optimization (PO) algorithms on LLM alignment is a challenging task that presents prohibitive costs, noise, and several variables like model size and hyper-pa…
Learning mirror maps in policy mirror descent
Carlo Alfano, Sebastian Towers, Silvia Sapora +2
Policy Mirror Descent (PMD) is a popular framework in reinforcement learning, serving as a unifying perspective that encompasses numerous algorithms. These algorithms are derived t…
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
Carlo Alfano, Rui Yuan, Patrick Rebeschini
Modern policy optimization methods in reinforcement learning, such as TRPO and PPO, owe their success to the use of parameterized policies. However, while theoretical guarantees ha…
Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization
Carlo Alfano, Patrick Rebeschini
We analyze the convergence rate of the unregularized natural policy gradient algorithm with log-linear policy parametrizations in infinite-horizon discounted Markov decision proces…
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning
Carlo Alfano, Patrick Rebeschini
Cooperative multi-agent reinforcement learning is a decentralized paradigm in sequential decision making where agents distributed over a network iteratively collaborate with neighb…