Multilingual Word Embeddings
19 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
Multilingual Word Embeddings for Low-Resource Languages using Anchors and a Chain of Related Languages
In this paper, we propose to build multilingual word embeddings (MWEs) via a novel language chain-based approach, that incorporates intermediate related languages to bridge the gap between the distant source and target.
A Primer on Pretrained Multilingual Language Models
Multilingual Language Models (\MLLMs) such as mBERT, XLM, XLM-R, \textit{etc.}
Bootstrapping Multilingual AMR with Contextual Word Alignments
We develop high performance multilingualAbstract Meaning Representation (AMR) sys-tems by projecting English AMR annotationsto other languages with weak supervision.
SHIKEBLCU at SemEval-2020 Task 2: An External Knowledge-enhanced Matrix for Multilingual and Cross-Lingual Lexical Entailment
In our system, we expand the number of external constraints in multiple languages to obtain more specialised multilingual word embeddings.
Line-a-line: A Tool for Annotating Word-Alignments
We here describe line-a-line, a web-based tool for manual annotation of word-alignments in sentence-aligned parallel corpora.
A Comparison of Architectures and Pretraining Methods for Contextualized Multilingual Word Embeddings
The lack of annotated data in many languages is a well-known challenge within the field of multilingual natural language processing (NLP).
Learning Unsupervised Multilingual Word Embeddings with Incremental Multilingual Hubs
We learn a shared multilingual embedding space for a variable number of languages by incrementally adding new languages one by one to the current multilingual space.
EusDisParser: improving an under-resourced discourse parser with cross-lingual data
More precisely, we build a monolingual system using the small set of data available and investigate the use of multilingual word embeddings to train a system for Basque using data annotated for another language.
Learning Multilingual Word Embeddings Using Image-Text Data
There has been significant interest recently in learning multilingual word embeddings -- in which semantically similar words across languages have similar embeddings.
Zero-Shot Cross-Lingual Opinion Target Extraction
In this work, we address the lack of available annotated data for specific languages by proposing a zero-shot cross-lingual approach for the extraction of opinion target expressions.
