activity
20202023
most citedParticipatory Research for Low-resourced Machine Translation: A Case Study in African Languages

7 citations · 16 across the 4 of their papers we have counts for

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8 papers · 1 filter

cs.CL2023

AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages

Jiayi Wang, David Ifeoluwa Adelani, Sweta Agrawal +55

Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, s…

cs.CL20235 cited

ChatGPT MT: Competitive for High- (but not Low-) Resource Languages

Nathaniel R. Robinson, Perez Ogayo, David R. Mortensen +1

Large language models (LLMs) implicitly learn to perform a range of language tasks, including machine translation (MT). Previous studies explore aspects of LLMs' MT capabilities. H…

cs.CL20231 cited

Multi-lingual and Multi-cultural Figurative Language Understanding

Anubha Kabra, Emmy Liu, Simran Khanuja +6

Figurative language permeates human communication, but at the same time is relatively understudied in NLP. Datasets have been created in English to accelerate progress towards meas…

cs.CL20231 cited

MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African Languages

Cheikh M. Bamba Dione, David Adelani, Peter Nabende +41

In this paper, we present MasakhaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages. We discuss the challenges in annotating POS for these…

cs.CL20223 cited

MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition

David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder +42

African languages are spoken by over a billion people, but are underrepresented in NLP research and development. The challenges impeding progress include the limited availability o…

cs.CL20221 cited

Quality-Aware Decoding for Neural Machine Translation

Patrick Fernandes, António Farinhas, Ricardo Rei +4

Despite the progress in machine translation quality estimation and evaluation in the last years, decoding in neural machine translation (NMT) is mostly oblivious to this and center…