数据集:

metaeval/temporal-nli

许可:

apache-2.0
英文
@inproceedings{thukral-etal-2021-probing,
    title = "Probing Language Models for Understanding of Temporal Expressions",
    author = "Thukral, Shivin  and
      Kukreja, Kunal  and
      Kavouras, Christian",
    booktitle = "Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.blackboxnlp-1.31",
    doi = "10.18653/v1/2021.blackboxnlp-1.31",
    pages = "396--406",
    abstract = "We present three Natural Language Inference (NLI) challenge sets that can evaluate NLI models on their understanding of temporal expressions. More specifically, we probe these models for three temporal properties: (a) the order between points in time, (b) the duration between two points in time, (c) the relation between the magnitude of times specified in different units. We find that although large language models fine-tuned on MNLI have some basic perception of the order between points in time, at large, these models do not have a thorough understanding of the relation between temporal expressions.",
}
对以上内容翻译成中文,不要翻译大写的英文, 保留a标签以及所有属性,按照此约束返回翻译后的中文
@inproceedings{thukral-etal-2021-probing,
    title = "Probing Language Models for Understanding of Temporal Expressions",
    author = "Thukral, Shivin  and
      Kukreja, Kunal  and
      Kavouras, Christian",
    booktitle = "Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.blackboxnlp-1.31",
    doi = "10.18653/v1/2021.blackboxnlp-1.31",
    pages = "396--406",
    abstract = "We present three Natural Language Inference (NLI) challenge sets that can evaluate NLI models on their understanding of temporal expressions. More specifically, we probe these models for three temporal properties: (a) the order between points in time, (b) the duration between two points in time, (c) the relation between the magnitude of times specified in different units. We find that although large language models fine-tuned on MNLI have some basic perception of the order between points in time, at large, these models do not have a thorough understanding of the relation between temporal expressions.",
}