[PDF] Data|Efficient Cross|Lingual Transfer with Language|Specific ...

Data-Efficient Cross-Lingual Transfer with Language-Specific ... - arXiv

Abstract page for arXiv paper 2211.00106: Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks.

[PDF] Data-Efficient Cross-Lingual Transfer with Language-Specific ...

Novel methods for using language-specific subnetworks, which control cross-lingual parameter sharing, to reduce conflicts and increase positive transfer ...

Cross-Lingual Transfer with Language-Specific Subnetworks for ...

Given our focus on low-resource languages, we also combine our methods with meta-learning, a data-efficient technique to learn tasks from a few samples (Finn,.

Data-Efficient Cross-Lingual Transfer with Language-Specific ...

Request PDF | Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks | Large multilingual language models typically share their parameters ...

Cross-Lingual Transfer with Language-Specific Subnetworks for ...

Given our focus on low-resource languages, we also combine our methods with meta-learning, a data-efficient technique to learn tasks from a few samples (Finn, ...

Efficiently Aligned Cross-Lingual Transfer Learning for ...

Cross-lingual transfer of language models trained on high-resource languages like En- glish has been widely studied for many NLP.

Parameter-Efficient Cross-lingual Transfer of Vision and Language ...

We propose a new parameter-efficient cross-lingual transfer learning framework that utilizes a translation-based alignment method to mitigate multilingual ...

Cross-Lingual Transfer with Language-Specific Subnetworks for ...

PDF | Large multilingual language models typically share their parameters across all languages, which enables cross-lingual task transfer, but learning.

Cross-lingual Language Model Pretraining - NIPS

We propose two methods to learn cross-lingual language models (XLMs): one unsu- pervised that only relies on monolingual data, and one supervised that leverages.

GreenPLM: Cross-Lingual Transfer of Monolingual Pre-Trained ...

Large pre-trained models have revolutionized nat- ural language processing (NLP) research and ap- plications, but high training costs and limited data resources ...

Language Fusion for Parameter-Efficient Cross-lingual Transfer

Language Fusion for Parameter-Efficient Cross-lingual Transfer. Download PDF. ACL ARR 2024 June Submission1738 Authors. 14 Jun 2024 (modified ...

[PDF] Efficient Language Model Training through Cross-Lingual and ...

A cross-lingual and progressive transfer learning approach that transfers models from a source language, for which pretrained models are publicly available, ...

Exploring Cross-Lingual Transfer to Counteract Data Scarcity for ...

sented through a source language (sometimes also called a transfer language) and the target domain through a specific target language and which may help ...

Make the Best of Cross-lingual Transfer: Evidence from POS ...

labelled data does not exist. 029. Cross-lingual generalisability of large pre-. 030 trained language models is ...

Choosing Transfer Languages for Cross-Lingual Learning

is that data in a high-resource transfer language is used to improve performance on a low-resource task language. However, determining the best transfer lan-.

Cross-Lingual Syntactic Transfer with Limited Resources

Translation data. We have translation data for all language pairs. We use Bi,j to refer to transla- tion data for the language pair (i, j) where i, j ∈. {1 ...

Cross-lingual Transfer Learning with Data Selection for Large-Scale ...

A typical approach is to pre-train the model on labeled data from a richly re- sourced language, and then either apply it directly on a target language ( ...

Cross-Lingual Transfer Learning for Phrase Break Prediction with ...

task-specific data is essentially required. ... with a modest number of target language instances in conjunc- tion with the source language data.

Evaluating the Cross-Lingual Effectiveness of Massively Multilingual ...

The evaluation metric used is classifi- cation accuracy. We use this data for both in-language train- ing and zero-shot transfer. The task-specific network and ...

Cross-lingual Few-Shot Learning on Unseen Languages

specific annotated data for a given target language. ∗ The authors ... Cross-lingual Transfer The effectiveness of cross-language transfer with ...