Reducing Hallucinations in Entity Abstract Summarization with Facts-Template Decomposition

arXiv:2402.18873v1 Announce Type: new
Abstract: Entity abstract summarization aims to generate a coherent description of a given entity based on a set of relevant Internet documents. Pretrained language models (PLMs) have achieved significant success in this task, but they may suffer from hallucinations, i.e. generating non-factual information about the entity. To address this issue, we decompose the summary into two components: Facts that represent the factual information about the given entity, which PLMs are prone to fabricate; and Template that …

abstract arxiv cs.cl documents facts generate hallucinations information internet language language models set success summarization template type