EditSR: Enhancing Neural Symbolic Regression via Edit-based Rectification 事件

EditSR: Enhancing Neural Symbolic Regression via Edit-based Rectification arXiv:2606.07915v1 Announce Type: new Abstract: Neural symbolic regression models improve inference efficiency by shifting structural search to pretraining, but their one-pass autoregressive decoding is prone to error accumulation, which may lead to generating structurally incorrect expressions, especially in complex expression generation scenarios. Existing rectification strategies can alleviate this issue, but they ofte