5 papers
The Path Matters: Learning a Token-Commitment Policy for Diffusion Language Models
Bohang Sun, Max Zhu, Francesco Caso +5
Diffusion large language models promise faster generation by refining many token positions in parallel, but this parallelism introduces a hidden control problem: which proposed tok…
Entropy-Lens: Uncovering Decision Strategies in LLMs
Riccardo Ali, Francesco Caso, Christopher Irwin +1
In large language models (LLMs), each block operates on the residual stream to map input token sequences to output token distributions. However, most of the interpretability litera…
Symmetry and Generalisation in Neural Approximations of Renormalisation Transformations
Cassidy Ashworth, Pietro Liò, Francesco Caso
Deep learning models have proven enormously successful at using multiple layers of representation to learn relevant features of structured data. Encoding physical symmetries into t…
Link Prediction with Physics-Inspired Graph Neural Networks
Andrea Giuseppe Di Francesco, Francesco Caso, Maria Sofia Bucarelli +1
The message-passing mechanism underlying Graph Neural Networks (GNNs) is not naturally suited for heterophilic datasets, where adjacent nodes often have different labels. Most solu…
Renormalized Graph Representations for Node Classification
Francesco Caso, Giovanni Trappolini, Andrea Bacciu +2
Graph neural networks process information on graphs represented at a given resolution scale. We analyze the effect of using different coarse-grained graph resolutions, obtained thr…