Search Results for author:
Found 2 papers, 0 papers with code
To Err Is Human, but Llamas Can Learn It Too
This study explores enhancing grammatical error correction (GEC) through artificial error generation (AEG) using language models (LMs).
Autocorrect for Estonian texts: final report from project EKTB25
To mitigate this, (1) we annotated more correction data for model training and testing, (2) we tested transfer-learning, i. e. retraining machine learning models created for other tasks, so as not to depend solely on correction data, (3) we compared the developed method and model with alternatives, including large language models.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
