10 papers
On the Creativity of AI Agents
Giorgio Franceschelli, Mirco Musolesi
Large language models (LLMs), particularly when integrated into agentic systems, have demonstrated human- and even superhuman-level performance across multiple domains. Whether the…
Complexity-Regularized Proximal Policy Optimization
Luca Serfilippi, Giorgio Franceschelli, Antonio Corradi +1
Policy gradient methods usually rely on entropy regularization to prevent premature convergence. However, maximizing entropy indiscriminately pushes the policy towards a uniform di…
DiffSampling: Enhancing Diversity and Accuracy in Neural Text Generation
Giorgio Franceschelli, Mirco Musolesi
Despite their growing capabilities, language models still frequently reproduce content from their training data, generate repetitive text, and favor common grammatical patterns and…
Thinking Outside the (Gray) Box: A Context-Based Score for Assessing Value and Originality in Neural Text Generation
Giorgio Franceschelli, Mirco Musolesi
Despite the increasing use of large language models for creative tasks, their outputs often lack diversity. Common solutions, such as sampling at higher temperatures, can compromis…
Quantum Chemistry Driven Molecular Inverse Design with Data-free Reinforcement Learning
Francesco Calcagno, Luca Serfilippi, Giorgio Franceschelli +3
The inverse design of molecules has challenged chemists for decades. In the past years, machine learning and artificial intelligence have emerged as new tools to generate molecules…
Training Foundation Models as Data Compression: On Information, Model Weights and Copyright Law
Giorgio Franceschelli, Claudia Cevenini, Mirco Musolesi
The training process of foundation models as for other classes of deep learning systems is based on minimizing the reconstruction error over a training set. For this reason, they a…