2026
Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment
ICML 2026poster
Despite their strong general capabilities, large language models (LLMs) often remain unreliable when outputs must be numerically precise. A key reason is the training objective: standard cross-entropy treats numeric tokens as unstructured categories and ignores the metric structure of their values. …