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cs.LG2025
ABS: Enforcing Constraint Satisfaction On Generated Sequences Via Automata-Guided Beam Search
Vincenzo Collura, Karim Tit, Laura Bussi +2
Sequence generation and prediction form a cornerstone of modern machine learning, with applications spanning natural language processing, program synthesis, and time-series forecas…
cs.LG2025
On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses
Mohamed Djilani, Thibault Simonetto, Karim Tit +4
Recent tabular Foundational Models (FM) such as TabPFN and TabICL, leverage in-context learning to achieve strong performance without gradient updates or fine-tuning. However, thei…