3 papers
cs.LG2026
Differentiable Lifting for Topological Neural Networks
Jorge Luiz Franco, Gabriel Duarte, Alexander Nikitin +3
Topological neural networks (TNNs) enable leveraging high-order structures on graphs (e.g., cycles and cliques) to boost the expressive power of message-passing neural networks. In…
cs.CL2026
MATH-PT: A Math Reasoning Benchmark for European and Brazilian Portuguese
Tiago Teixeira, Ana Carolina Erthal, Juan Belieni +5
The use of large language models (LLMs) for complex mathematical reasoning is an emergent area of research, with fast progress in methods, models, and benchmark datasets. However,…
cs.LG2025
Cooperative Sheaf Neural Networks
André Ribeiro, Ana Luiza Tenório, Juan Belieni +2
Sheaf diffusion has recently emerged as a promising design pattern for graph representation learning due to its inherent ability to handle heterophilic data and avoid oversmoothing…