arXiv cs.AI
· Papers
Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning
arXiv:2604.21495v2 Announce Type: replace-cross Abstract: Numerical reasoning over expert-domain tables often exhibits high in-domain accuracy but limited robustness to domain shift. Models trained with supervised fine-tuning (SFT) on specific datasets tend to rely on header-operation shortcuts rather than structural r