Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Cross-Lingual Embedding Methods and Applications: A Systematic Review for Low-Resourced Scenarios

Domain:

natural language processing

Record type:

paperposter

Cross-Lingual Embedding Methods and Applications: A Systematic Review for Low-Resourced Scenarios

Poster presented at the Deep Learning Indaba 2022 by Thapelo Andrew Sindane

Visit

storage.googleapis.com

Tasks

embeddings

Tags

deep learning indabaposterdlideep learning indaba 2022

Similar

Multimodal Embedding Integration for Cross-Lingual NER in Low-Resource LanguagesEnhancing Cross-lingual Sentence Embedding for Low-resource Languages with Word AlignmentArtificial Code-Switching for Cross-Lingual Embedding Alignment in Low-Resource Languagessangeet2020/Cross-lingual-topic-identification-in-low-resource-scenariosCan Embedding Similarity Predict Cross-Lingual Transfer? A Systematic Study on African LanguagesCross-lingual Embedding Clustering for Hierarchical Softmax in Low-Resource Multilingual Speech Recognition

Multimodal Embedding Integration for Cross-Lingual NER in Low-Resource Languages

Cross-lingual Named Entity Recognition (NER) leverages knowledge transfer between languages to ident

Enhancing Cross-lingual Sentence Embedding for Low-resource Languages with Word Alignment

The field of cross-lingual sentence embeddings has recently experienced significant advancements, bu

Artificial Code-Switching for Cross-Lingual Embedding Alignment in Low-Resource Languages

Transferring information retrieval (IR) models from a high-resource language (typically English) to

sangeet2020/Cross-lingual-topic-identification-in-low-resource-scenarios

Topic prediction for low-resource language # Cross-lingual topic identification in low resource sce

Can Embedding Similarity Predict Cross-Lingual Transfer? A Systematic Study on African Languages

Cross-lingual transfer is essential for building NLP systems for low-resource African languages, but

Cross-lingual Embedding Clustering for Hierarchical Softmax in Low-Resource Multilingual Speech Recognition

We present a novel approach centered on the decoding stage of Automatic Speech Recognition (ASR) tha