21 citations · 55 across the 7 of their papers we have counts for
7 papers
Multilingual Word Embeddings for Low-Resource Languages using Anchors and a Chain of Related Languages
Viktor Hangya, Silvia Severini, Radoslav Ralev +2
Very low-resource languages, having only a few million tokens worth of data, are not well-supported by multilingual NLP approaches due to poor quality cross-lingual word representa…
Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages
Ayyoob Imani, Peiqin Lin, Amir Hossein Kargaran +8
The NLP community has mainly focused on scaling Large Language Models (LLMs) vertically, i.e., making them better for about 100 languages. We instead scale LLMs horizontally: we cr…
Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging
Ayyoob Imani, Silvia Severini, Masoud Jalili Sabet +2
Part-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS…
SilverAlign: MT-Based Silver Data Algorithm For Evaluating Word Alignment
Abdullatif Köksal, Silvia Severini, Hinrich Schütze
Word alignments are essential for a variety of NLP tasks. Therefore, choosing the best approaches for their creation is crucial. However, the scarce availability of gold evaluation…
Don't Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings
Silvia Severini, Viktor Hangya, Masoud Jalili Sabet +2
Bilingual Word Embeddings (BWEs) are one of the cornerstones of cross-lingual transfer of NLP models. They can be built using only monolingual corpora without supervision leading t…
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages
Silvia Severini, Ayyoob Imani, Philipp Dufter +1
Parallel corpora are ideal for extracting a multilingual named entity (MNE) resource, i.e., a dataset of names translated into multiple languages. Prior work on extracting MNE data…
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing
Ahmed Elnaggar, Wei Ding, Llion Jones +6
Currently, a growing number of mature natural language processing applications make people's life more convenient. Such applications are built by source code - the language in soft…