184 citations · 210 across the 3 of their papers we have counts for
7 papers · 1 filter
Adapters for Altering LLM Vocabularies: What Languages Benefit the Most?
HyoJung Han, Akiko Eriguchi, Haoran Xu +3
Vocabulary adaptation, which integrates new vocabulary into pre-trained language models, enables expansion to new languages and mitigates token over-fragmentation. However, existin…
X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale
Haoran Xu, Kenton Murray, Philipp Koehn +3
Large language models (LLMs) have achieved remarkable success across various NLP tasks with a focus on English due to English-centric pre-training and limited multilingual data. In…
XLM-T: Scaling up Multilingual Machine Translation with Pretrained Cross-lingual Transformer Encoders
Shuming Ma, Jian Yang, Haoyang Huang +10
Multilingual machine translation enables a single model to translate between different languages. Most existing multilingual machine translation systems adopt a randomly initialize…
Neural Text Generation with Artificial Negative Examples
Keisuke Shirai, Kazuma Hashimoto, Akiko Eriguchi +2
Neural text generation models conditioning on given input (e.g. machine translation and image captioning) are usually trained by maximum likelihood estimation of target text. Howev…
Multilingual Extractive Reading Comprehension by Runtime Machine Translation
Akari Asai, Akiko Eriguchi, Kazuma Hashimoto +1
Despite recent work in Reading Comprehension (RC), progress has been mostly limited to English due to the lack of large-scale datasets in other languages. In this work, we introduc…
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation
Akiko Eriguchi, Melvin Johnson, Orhan Firat +2
Transferring representations from large supervised tasks to downstream tasks has shown promising results in AI fields such as Computer Vision and Natural Language Processing (NLP).…