Tag
Introduces a framework combining flow-based generative editing with evolutionary algorithms to perform optimization in residual space, enabling controllable data editing with non-differentiable objectives. Validated on MorphoMNIST and crystal data.
Proposes CoCoGEC, a counterfactual generation framework that alters error-irrelevant contexts in GEC training data to improve model robustness, achieving significant F0.5 gains on perturbed benchmarks.