Evaluating Prompting Strategies for Grammatical Error Correction Based on Language Proficiency (2024.lrec-main)
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| Challenge: | generative LLMs have been known for overcorrection where results obtain higher recall measures than precision measures. |
| Approach: | They propose to use generative LLMs to prompt grammatical error correction using a model based on language proficiency to examine the interaction between LLM's performance and L2 language proficiency. |
| Outcome: | The proposed model improves on zero-shot and few-shot prompting and fine-tuning models for grammatical error correction for learners of English as a foreign language based on the different proficiency levels. |
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| Challenge: | Grammatical error correction (GEC) aims to correct grammatical, spelling, and semantic errors in natural language text. |
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