Browse > Natural Language Processing > Cross-Lingual > Cross-Lingual Transfer

Cross-Lingual Transfer

34 papers with code · Natural Language Processing
Subtask of Cross-Lingual

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Unsupervised Cross-lingual Representation Learning at Scale

5 Nov 2019huggingface/transformers

We also present a detailed empirical analysis of the key factors that are required to achieve these gains, including the trade-offs between (1) positive transfer and capacity dilution and (2) the performance of high and low resource languages at scale.

CROSS-LINGUAL TRANSFER LANGUAGE MODELLING REPRESENTATION LEARNING

XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization

24 Mar 2020google-research/xtreme

However, these broad-coverage benchmarks have been mostly limited to English, and despite an increasing interest in multilingual models, a benchmark that enables the comprehensive evaluation of such methods on a diverse range of languages and tasks is still missing.

CROSS-LINGUAL TRANSFER

Don't Just Scratch the Surface: Enhancing Word Representations for Korean with Hanja

IJCNLP 2019 shin285/KOMORAN

We propose a simple yet effective approach for improving Korean word representations using additional linguistic annotation (i. e. Hanja).

CROSS-LINGUAL TRANSFER TRANSFER LEARNING

Cross-Lingual Natural Language Generation via Pre-Training

23 Sep 2019CZWin32768/xnlg

In this work we focus on transferring supervision signals of natural language generation (NLG) tasks between multiple languages.

ABSTRACTIVE TEXT SUMMARIZATION CROSS-LINGUAL TRANSFER MACHINE TRANSLATION QUESTION GENERATION TEXT GENERATION

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

ACL 2019 microsoft/Multilingual-Model-Transfer

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.

CROSS-LINGUAL TRANSFER TEXT CLASSIFICATION TRANSFER LEARNING

Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialog

NAACL 2019 sz128/NLU_DST_datasets

We use this data set to evaluate three different cross-lingual transfer methods: (1) translating the training data, (2) using cross-lingual pre-trained embeddings, and (3) a novel method of using a multilingual machine translation encoder as contextual word representations.

CROSS-LINGUAL TRANSFER MACHINE TRANSLATION TRANSFER LEARNING

Choosing Transfer Languages for Cross-Lingual Learning

ACL 2019 neulab/langrank

Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.

CROSS-LINGUAL TRANSFER

Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification

TACL 2018 ccsasuke/adan

To tackle the sentiment classification problem in low-resource languages without adequate annotated data, we propose an Adversarial Deep Averaging Network (ADAN) to transfer the knowledge learned from labeled data on a resource-rich source language to low-resource languages where only unlabeled data exists.

CROSS-LINGUAL DOCUMENT CLASSIFICATION CROSS-LINGUAL SENTIMENT CLASSIFICATION CROSS-LINGUAL TRANSFER SENTIMENT ANALYSIS