3 papers
cs.DS2025
Sequence graphs realizations and ambiguity in language models
Sammy Khalife, Yann Ponty, Laurent Bulteau
Several popular language models represent local contexts in an input text as bags of words. Such representations are naturally encoded by a sequence graph whose vertices are th…
math.OC2025
How hard is learning to cut? Trade-offs and sample complexity
Sammy Khalife, Andrea Lodi
In the recent years, branch-and-cut algorithms have been the target of data-driven approaches designed to enhance the decision making in different phases of the algorithm such as b…
cs.LG2024
Is uniform expressivity too restrictive? Towards efficient expressivity of graph neural networks
Sammy Khalife, Josué Tonelli-Cueto
Uniform expressivity guarantees that a Graph Neural Network (GNN) can express a query without the parameters depending on the size of the input graphs. This property is desirable i…