Quantifying Error Tolerance in Synthetic Data: An Atomic-level Operand vs. Operator Perturbation Study
By prioritizing operator over aggressive operand precision, the ATOM-synthesized data outperforms rigorous baselines (e.g., +3.1% gain over LIMA), suggesting that operator diversity matters more than operand precision.
Jia-Xiang Liu, Chenhao Yuan, Shunnan Xu et al.
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