Native Language Identification

5 papers with code • 1 benchmarks • 2 datasets

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).

Most implemented papers

A study of N-gram and Embedding Representations for Native Language Identification

nishkalavallabhi/NLIST2017 WS 2017

We report on our experiments with N-gram and embedding based feature representations for Native Language Identification (NLI) as a part of the NLI Shared Task 2017 (team name: NLI-ISU).

On the Development of a Large Scale Corpus for Native Language Identification

ghomasHudson/italkiCorpus TLT17 2018

It can be used for training machine learning based systems for classifying and identifying the native language of authors of English text.

Towards Ethical Content-Based Detection of Online Influence Campaigns

ecrows/l2-reddit-experiment 29 Aug 2019

The detection of clandestine efforts to influence users in online communities is a challenging problem with significant active development.

Topics to Avoid: Demoting Latent Confounds in Text Classification

Sachin19/adversarial-classify IJCNLP 2019

Despite impressive performance on many text classification tasks, deep neural networks tend to learn frequent superficial patterns that are specific to the training data and do not always generalize well.

Native Language Identification with Big Bird Embeddings

sergeykramp/mthesis-bigbird-embeddings 13 Sep 2023

Native Language Identification (NLI) intends to classify an author's native language based on their writing in another language.