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20172022
most citedOn Optimal Transformer Depth for Low-Resource Language Translation

20 citations · 58 across the 12 of their papers we have counts for

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cs.CL2022

Intriguing Properties of Compression on Multilingual Models

Kelechi Ogueji, Orevaoghene Ahia, Gbemileke Onilude +3

Multilingual models are often particularly dependent on scaling to generalize to a growing number of languages. Compression techniques are widely relied upon to reconcile the growt…

cs.CL2022

Domain Curricula for Code-Switched MT at MixMT 2022

Lekan Raheem, Maab Elrashid

In multilingual colloquial settings, it is a habitual occurrence to compose expressions of text or speech containing tokens or phrases of different languages, a phenomenon popularl…

cs.CL2022

JoeyS2T: Minimalistic Speech-to-Text Modeling with JoeyNMT

Mayumi Ohta, Julia Kreutzer, Stefan Riezler

JoeyS2T is a JoeyNMT extension for speech-to-text tasks such as automatic speech recognition and end-to-end speech translation. It inherits the core philosophy of JoeyNMT, a minima…

cs.CL2021

Bandits Don't Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits

Julia Kreutzer, David Vilar, Artem Sokolov

Training data for machine translation (MT) is often sourced from a multitude of large corpora that are multi-faceted in nature, e.g. containing contents from multiple domains or di…

cs.CL2021

The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation

Orevaoghene Ahia, Julia Kreutzer, Sara Hooker

A "bigger is better" explosion in the number of parameters in deep neural networks has made it increasingly challenging to make state-of-the-art networks accessible in compute-rest…

cs.CL20218 cited

Evaluating Multiway Multilingual NMT in the Turkic Languages

Jamshidbek Mirzakhalov, Anoop Babu, Aigiz Kunafin +11

Despite the increasing number of large and comprehensive machine translation (MT) systems, evaluation of these methods in various languages has been restrained by the lack of high-…