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 …

The rapid progress of research aimed at interpreting the inner workings of advanced
language models has highlighted a need for contextualizing the insights gained from years …

Hallucinations in machine translation are translations that contain information completely
unrelated to the input. Omissions are translations that do not include some of the input …

Hallucination is a significant barrier to the utilization of large-scale language models or
multimodal models. In this study, we collected 654 computer science papers with" …

Ideally, dialogue systems should generate responses that are faithful to the knowledge
contained in relevant documents. However, many models generate hallucinated responses …

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 …

Despite the remarkable performance of generative large language models (LLMs) on
abstractive summarization, they face two significant challenges: their considerable size and …

When the amount of parallel sentences available to train a neural machine translation is
scarce, a common practice is to generate new synthetic training samples from them. A …

Information extraction (IE) is an important task in Natural Language Processing (NLP),
involving the extraction of named entities and their relationships from unstructured text. In …

Document-level event factuality identification (DEFI) assesses the veracity degree to which
an event mentioned in a document has happened, which is crucial for many natural …