Kwabena Amponsah-Kaakyire

According to our database, Kwabena Amponsah-Kaakyire authored at least 5 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Explaining Translationese: why are Neural Classifiers Better and what do they Learn?

Kwabena Amponsah-Kaakyire, Daria Pylypenko, Josef van Genabith, Cristina España-Bonet

Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

2021

Findings of the 2021 Conference on Machine Translation (WMT21).

Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondrej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-jussà, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, Marcos Zampieri

Proceedings of the Sixth Conference on Machine Translation, 2021

Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification.

Daria Pylypenko, Kwabena Amponsah-Kaakyire, Koel Dutta Chowdhury, Josef van Genabith, Cristina España-Bonet

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of Yorùbá and Twi.

Jesujoba O. Alabi, Kwabena Amponsah-Kaakyire, David Ifeoluwa Adelani, Cristina España-Bonet

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

2019

Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi.

Jesujoba O. Alabi, Kwabena Amponsah-Kaakyire, David Ifeoluwa Adelani, Cristina España-Bonet

CoRR, 2019