Factual Correctness

AbstractMachine Reading Comprehension (MRC) is the task of answering a question over a paragraph of text. While neural MRC systems gain popularity and achieve noticeable performance, issues are being raised …...

Text summarization is an important yet chal- lenging task in natural language processing. In this paper, we investigate Pointer Genera- tor Networks for sentence compression. Using Vietnamese as a case …...

AbstractNeural abstractive summarization models are able to generate summaries which have high overlap with human references. However, existing models are not optimized for factual correctness, a critical metric in real-world …...

AbstractDialogue summarization is abstractive in nature, making it suffer from factual errors. The factual correctness of summaries has the highest priority before practical applications. Many efforts have been made to …...

AbstractFactual correctness is often the limiting factor in practical applications of natural language generation in high-stakes domains such as healthcare. An essential requirement for maintaining factuality is the ability to …...