Machine translation systems achieve near human-level performance on some languages,
yet their effectiveness strongly relies on the availability of large amounts of parallel …

We audit how hallucination in large language models (LLMs) is characterized in peer-
reviewed literature, using a critical examination of 103 publications across NLP research …

Neural Machine Translation (NMT) brings promising improvements in translation quality, but
until recently, these models rely on large-scale parallel corpora. As such corpora only exist …

We investigate how hallucination in large language models (LLM) is characterized in peer-
reviewed literature using a critical examination of 103 publications across NLP research …

Abstract Domain adaptation is an active field of research in statistical machine translation
(SMT), but so far most work has ignored the distinction between the topic and genre of …

Recent unsupervised machine translation (UMT) systems usually employ three main
principles: initialization, language modeling and iterative back-translation, though they may …

Abstract The multilingual Paraphrase Database (PPDB) is a freely available automatically
created resource of paraphrases in multiple languages. In statistical machine translation …

In this paper we explore a Japanese news simplification task. We designed a Japanese
news simplification task, constructed the data set for the task, and analyzed the manual …

It is widely accepted that translating user-generated (UG) text is a difficult task for modern
statistical machine translation (SMT) systems. The translation quality metrics typically used …

ABSTRACT The advent of Large Language Models (LLMs) has ushered in a new era of
possibilities in artificial intelligence, yet it has also introduced the challenge of hallucinations …