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Found 12 papers, 7 papers with code
Few-Shot Pidgin Text Adaptation via Contrastive Fine-Tuning
The surging demand for multilingual dialogue systems often requires a costly labeling process for each language addition.
AAdaM at SemEval-2024 Task 1: Augmentation and Adaptation for Multilingual Semantic Textual Relatedness
This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages.
The Hidden Space of Transformer Language Adapters
We analyze the operation of transformer language adapters, which are small modules trained on top of a frozen language model to adapt its predictions to new target languages.
The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis
Compared to work on monolingual (English) in-context learning, multilingual in-context learning is under-explored, and we lack an in-depth understanding of the role of demonstrations in this context.
SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects
Despite the progress we have recorded in the last few years in multilingual natural language processing, evaluation is typically limited to a small set of languages with available datasets which excludes a large number of low-resource languages.
YORC: Yoruba Reading Comprehension dataset
In this paper, we create YORC: a new multi-choice Yoruba Reading Comprehension dataset that is based on Yoruba high-school reading comprehension examination.
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users.
MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
African languages are spoken by over a billion people, but are underrepresented in NLP research and development.
Separating Grains from the Chaff: Using Data Filtering to Improve Multilingual Translation for Low-Resourced African Languages
We participated in the WMT 2022 Large-Scale Machine Translation Evaluation for the African Languages Shared Task.
Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning
Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks for both high-resourced and low-resourced languages.
The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation
We investigate how and when this training condition affects the final quality and intelligibility of a translation.
Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi
In this paper we focus on two African languages, Yor\`ub\'a and Twi, and compare the word embeddings obtained in this way, with word embeddings obtained from curated corpora and a language-dependent processing.
