将纠错拆成有类型阶段，让每步修改更可解释。
STAGEET: Stage-wise Typed Edit Tagging for Grammatical Error Correction with Arabic as a Case Study
- 分阶段预测纠错类型，每阶段独立修正一次
- 在QALB-2014上达顶尖性能，比传统方法更可解释
- 适合需要透明纠错过程的研究与应用
序列到编辑（Seq2Edit）方法通过在输入上预测编辑标签实现语法错误纠正（GEC），具有高效和局部可解释性。然而其可解释性仅限于操作层面：标签仅说明字符串如何变化，单一编辑词汇表无法揭示纠正类型。我们提出STAGEET，一种分阶段的有类型编辑标记框架，将Seq2Edit的监督机制重构为有类型可执行阶段，并扩展编辑操作至纠错类别。STAGEET将纠错分解为有序的中粒度有类型阶段；每个阶段从自身标签空间预测，一次性重写当前假设，并将结果中间句传递给下一阶段。我们实现了两种版本：共享编码器多头模型配阶段专用适配器，以及每个阶段独立纠错器的全专用变体。在QALB-2014和ZAEBUC数据集上的实验表明，具备类别感知的分阶段纠正保持了竞争性的基于编辑的GEC性能，同时揭示了更可检查的纠正轨迹，并在QALB-2014上达到最新最佳结果。
原文摘要 · Abstract (English)
Sequence-to-edit approaches make grammatical error correction (GEC) efficient and locally interpretable by predicting edit labels over the input rather than generating a full corrected sentence. Their interpretability, however, is primarily operational: a label specifies how the string should change, but a single edit vocabulary does not always reveal the type of correction being made. We propose STAGEET, a stage-wise typed edit-tagging framework that reorganizes Seq2Edit supervision into typed executable stages and extends edit operations to correction categories. STAGEET decomposes correction into an ordered sequence of medium-grained typed stages; each stage predicts from its own label space, rewrites the current hypothesis once, and passes the resulting intermediate sentence to the next stage. We instantiate the framework as both an end-to-end shared-encoder multi-head model with stage-specific adapters and a fully specialized variant with one independent tagger per stage. Experiments on QALB-2014 and ZAEBUC show that category-aware staged correction retains competitive edit-based GEC performance while exposing a more inspectable correction trajectory, and attains state-of-the-art results on QALB-2014.
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