AI RESEARCH
Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning
arXiv CS.LG
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ArXi:2604.21495v1 Announce Type: new 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 reasoning. We