Tag
This paper introduces Digit Entropy Loss (DEL), a novel loss function for numerical learning in large language models that reformulates entropy optimization to improve digit-level prediction accuracy and handle floating-point numbers, consistently outperforming existing methods on mathematical reasoning benchmarks.