Cross-Lingual Transfer
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Greatest papers with code
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
We introduce an architecture to learn joint multilingual sentence representations for 93 languages, belonging to more than 30 different families and written in 28 different scripts.
CROSS-LINGUAL BITEXT MINING CROSS-LINGUAL DOCUMENT CLASSIFICATION CROSS-LINGUAL NATURAL LANGUAGE INFERENCE CROSS-LINGUAL TRANSFER DOCUMENT CLASSIFICATION JOINT MULTILINGUAL SENTENCE REPRESENTATIONS PARALLEL CORPUS MINING
Unsupervised Cross-lingual Representation Learning at Scale
We also present a detailed empirical evaluation 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
Cross-Lingual Natural Language Generation via Pre-Training
• CZWin32768/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
Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages
Morphological segmentation for polysynthetic languages is challenging, because a word may consist of many individual morphemes and training data can be extremely scarce.
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification
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 TRANSFER SENTIMENT ANALYSIS
Choosing Transfer Languages for Cross-Lingual Learning
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.
Massively Multilingual Transfer for NER
ACL 2019
• afshinrahimi/mmner
• 
In cross-lingual transfer, NLP models over one or more source languages are applied to a low-resource target language.
CROSS-LINGUAL TRANSFER FEW-SHOT LEARNING NAMED ENTITY RECOGNITION
Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework
ICLR 2020
• thespectrewithin/joint-align
•
We further show that our proposed framework can generalize to contextualized representations and achieves state-of-the-art results on the CoNLL cross-lingual NER benchmark.