3 papers
cs.LG2026
End-to-End Compression for Tabular Foundation Models
Guri Zabërgja, Rafiq Kamel, Arlind Kadra +2
The long-standing dominance of gradient-boosted decision trees for tabular data has recently been challenged by in-context learning tabular foundation models. In-context learning m…
cs.CL2025
SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation
Rafiq Kamel, Filippo Guerranti, Simon Geisler +1
Large Language Models (LLMs) are increasingly applied to tasks involving structured inputs such as graphs. Abstract Meaning Representations (AMRs), which encode rich semantics as d…
cs.LG2023
On the Adversarial Robustness of Graph Contrastive Learning Methods
Filippo Guerranti, Zinuo Yi, Anna Starovoit +3
Contrastive learning (CL) has emerged as a powerful framework for learning representations of images and text in a self-supervised manner while enhancing model robustness against a…