March 13, 2024, 4:43 a.m. | Jiuding Yang, Hui Liu, Weidong Guo, Zhuwei Rao, Yu Xu, Di Niu

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.07557v1 Announce Type: cross
Abstract: Ensuring factual consistency between the summary and the original document is paramount in summarization tasks. Consequently, considerable effort has been dedicated to detecting inconsistencies. With the advent of Large Language Models (LLMs), recent studies have begun to leverage their advanced language understanding capabilities for inconsistency detection. However, early attempts have shown that LLMs underperform traditional models due to their limited ability to follow instructions and the absence of an effective detection methodology. In this study, …

abstract advanced arxiv begun capabilities cs.cl cs.lg detection document however language language models language understanding large language large language models llm llms studies summarization summary tasks type understanding

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