Cross-Lingual NER

24 papers with code • 28 benchmarks • 9 datasets

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Most implemented papers

ByT5: Towards a token-free future with pre-trained byte-to-byte models

google-research/byt5 28 May 2021

Most widely-used pre-trained language models operate on sequences of tokens corresponding to word or subword units.

Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings

ikergarcia1996/Easy-Translate 23 Oct 2022

Zero-resource cross-lingual transfer approaches aim to apply supervised models from a source language to unlabelled target languages.

Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT

shijie-wu/crosslingual-nlp IJCNLP 2019

Pretrained contextual representation models (Peters et al., 2018; Devlin et al., 2018) have pushed forward the state-of-the-art on many NLP tasks.

Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework

thespectrewithin/joint-align ICLR 2020

Learning multilingual representations of text has proven a successful method for many cross-lingual transfer learning tasks.

Rethinking embedding coupling in pre-trained language models

PaddlePaddle/PaddleNLP ICLR 2021

We re-evaluate the standard practice of sharing weights between input and output embeddings in state-of-the-art pre-trained language models.

Frustratingly Easy Label Projection for Cross-lingual Transfer

edchengg/easyproject 28 Nov 2022

Translating training data into many languages has emerged as a practical solution for improving cross-lingual transfer.

T-Projection: High Quality Annotation Projection for Sequence Labeling Tasks

ikergarcia1996/t-projection 20 Dec 2022

In the absence of readily available labeled data for a given sequence labeling task and language, annotation projection has been proposed as one of the possible strategies to automatically generate annotated data.

Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark

opennlg/openba-v2 arXiv 2023

We introduce Universal NER (UNER), an open, community-driven project to develop gold-standard NER benchmarks in many languages.

Multi-Source Cross-Lingual Model Transfer: Learning What to Share

microsoft/Multilingual-Model-Transfer ACL 2019

In this work, we focus on the multilingual transfer setting where training data in multiple source languages is leveraged to further boost target language performance.

Entity Projection via Machine Translation for Cross-Lingual NER

alankarj/cross_lingual_ner IJCNLP 2019

Although over 100 languages are supported by strong off-the-shelf machine translation systems, only a subset of them possess large annotated corpora for named entity recognition.