Uncovering the Risks and Drawbacks Associated With the Use of Synthetic Data for Grammatical Error Correction
In a Data-Centric AI paradigm, the model performance is enhanced without altering the model architecture, as evidenced by real-world and benchmark dataset demonstrations. With the advancements of large language models (LLM), it has become increasingly feasible to generate high-quality synthetic data...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10234394/ |