论文标题
解释科学文件之间的关系
Explaining Relationships Between Scientific Documents
论文作者
论文摘要
我们解决了使用自然语言文本解释两个科学文档之间关系的任务。此任务需要对长技术文档的复杂内容进行建模，推论这些文档之间的关系，并在文本中表达该关系的细节。除了这项任务的理论兴趣外，成功的解决方案还可以帮助提高研究人员在搜索和审查方面的效率。在本文中，我们从154K文档中建立了一个622K示例的数据集。我们为大型语言模型提供了预算，可以作为完成任务的自回归方法的基础。我们探讨了对这两个文档的不同看法的影响，包括使用科学IE系统提取的密集表示。我们提供广泛的自动和人类评估，以显示这种模型的希望，但对未来的工作面临明确的挑战。
We address the task of explaining relationships between two scientific documents using natural language text. This task requires modeling the complex content of long technical documents, deducing a relationship between these documents, and expressing the details of that relationship in text. In addition to the theoretical interest of this task, successful solutions can help improve researcher efficiency in search and review. In this paper we establish a dataset of 622K examples from 154K documents. We pretrain a large language model to serve as the foundation for autoregressive approaches to the task. We explore the impact of taking different views on the two documents, including the use of dense representations extracted with scientific IE systems. We provide extensive automatic and human evaluations which show the promise of such models, but make clear challenges for future work.
