RILEC: Detection and Generation of L1 Russian Interference Errors in English Learner Texts
Many errors in student essays can be explained by influence from the native language (L1). L1 interference refers to errors influenced by a speaker's first language, such as using stadion instead of stadium, reflecting lexical transliteration from Russian. In this work, we address the task of detecting such errors in English essays written by Russian-speaking learners. We introduce RILEC, a large-scale dataset of over 18,000 sentences, combining expert-annotated data from REALEC with synthetic examples generated through rule-based and neural augmentation. We propose a framework for generating L1-motivated errors using generative language models optimized with PPO, prompt-based control, an...
| Authors | Darya Kharlamova, Irina Proskurina |
|---|---|
| Primary category | cs.CL |
| Published | 7 March 2026 |
| Last updated at source | 7 March 2026 |
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