Hallucinated translations can severely undermine and raise safety issues when machine
translation systems are deployed in the wild. Previous research on the topic focused on …

Hallucinations and off-target translation remain unsolved problems in machine translation,
especially for low-resource languages and massively multilingual models. In this paper, we …

Recent code translation techniques exploit neural machine translation models to translate
source code from one programming language to another to satisfy production compatibility …

The recently released NLLB-200 is a set of multilingual Neural Machine Translation models
that cover 202 languages. The largest model is based on a Mixture of Experts architecture …

Despite the growing variety of languages supported by existing multilingual neural machine
translation (MNMT) models, most of the world's languages are still being left behind. We aim …

This article introduces contrastive alignment instructions (AlignInstruct) to address two
challenges in machine translation (MT) on large language models (LLMs). One is the …

Gender bias is a significant issue in machine translation, leading to ongoing research efforts
in developing bias mitigation techniques. However, most works focus on debiasing bilingual …

Whisper is a multitask and multilingual speech model covering 99 languages. It yields
commendable automatic speech recognition (ASR) results in a subset of its covered …

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 …

The NLP community has recently witnessed the success of Large Language Models (LLMs)
across various Natural Language Processing (NLP) tasks. However, the potential of LLMs …