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Native Language Identification

Native Language Identification (NLI) is the task of determining an author's native language (L1) based only on their writings in a second language (L2).

Papers

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Showing 51–75 of 83 papers

TitleStatusHype
Native Language Identification using Phonetic Algorithms—0
Native Language Identification using Stacked Generalization—0
Native Language Identification With Classifier Stacking and Ensembles—0
Native-Language Identification with Attention—0
Native Language Identification with Large Language Models—0
Native Language Identification with PPM—0
Native Language Identification with User Generated Content—0
Native Tongues, Lost and Found: Resources and Empirical Evaluations in Native Language Identification—0
Neural Networks and Spelling Features for Native Language Identification—0
Norwegian Native Language Identification—0
Oracle and Human Baselines for Native Language Identification—0
Predicting Foreign Language Usage from English-Only Social Media Posts—0
Punctuation as Native Language Interference—0
Regression or classification? Automated Essay Scoring for Norwegian—0
Robust, Lexicalized Native Language Identification—0
Scaling Native Language Identification with Transformer Adapters—0
Simple Yet Powerful Native Language Identification on TOEFL11—0
Stacked Sentence-Document Classifier Approach for Improving Native Language Identification—0
String Kernels for Native Language Identification: Insights from Behind the Curtains—0
The MERLIN corpus: Learner language and the CEFR—0
The Power of Character N-grams in Native Language Identification—0
The Role of Emotions in Native Language Identification—0
Transductive Learning with String Kernels for Cross-Domain Text Classification—0
Turkish Native Language Identification—0
Unravelling Interlanguage Facts via Explainable Machine Learning—0
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