mlsanityData to 7 Oct 2026

Bi-DCSpell: A Bi-directional Detector-Corrector Interactive Framework for Chinese Spelling Check

arXiv 2406.01879 ↗First posted 4 Jun 2024cs.CLcited by 1

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Abstract (arXiv)

Chinese Spelling Check (CSC) aims to detect and correct potentially misspelled characters in Chinese sentences. Naturally, it involves the detection and correction subtasks, which interact with each other dynamically. Such interactions are bi-directional, i.e., the detection result would help reduce the risk of over-correction and under-correction while the knowledge learnt from correction would help prevent false detection. Current CSC approaches are of two types: correction-only or single-directional detection-to-correction interactive frameworks. Nonetheless, they overlook the bi-directional interactions between detection and correction. This paper aims to fill the gap by proposing a Bi-directional Detector-Corrector framework for CSC (Bi-DCSpell). Notably, Bi-DCSpell contains separate detection and correction encoders, followed by a novel interactive learning module facilitating bi-directional feature interactions between detection and correction to improve each other's representation learning. Extensive experimental results demonstrate a robust correction performance of Bi-DCSpell on widely used benchmarking datasets while possessing a satisfactory detection ability.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 10 of its 35 references that are in the map. First posted on arXiv 4 Jun 2024.

Builds on

10 of 35 references.

References · 10

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  4. 2017Decoupled Weight Decay Regularizationcited by 1,722
  5. 2020Spelling Error Correction with Soft-Masked BERTcited by 90
  6. 2021ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Informationcited by 65
  7. 2020SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Checkcited by 57
  8. 2021Read, Listen, and See: Leveraging Multimodal Information Helps Chinese Spell Checkingcited by 52
  9. 2023A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Checkcited by 15
  10. 2023Disentangled Phonetic Representation for Chinese Spelling Correctioncited by 14

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