Abstract
As part of the recent research effort on quantum natural language processing (QNLP), variational quantum sentence classifiers (VQSCs) have been implemented and supported in lambeq / DisCoPy, based on the DisCoCat model of sentence meaning. We discuss in some detail VQSCs, including category theory, DisCoCat for modeling sentence as string diagram, and DisCoPy for encoding string diagram as parameterized quantum circuit. Many NLP tasks, however, require the handling of text consisting of multiple sentences, which is not supported in lambeq / DisCoPy. A good example is sentiment classification of customer feedback or product review. We discuss three potential approaches to variational quantum text classifiers (VQTCs), in line with VQSCs. The first is a weighted bag-of-sentences approach which treats text as a group of independent sentences with task-specific sentence weighting. The second is a coreference resolution approach which treats text as a consolidation of its member sentences with coreferences among them resolved. Both approaches are based on the DisCoCat model and should be implementable in lambeq / DisCoCat. The third approach, on the other hand, is based on the DisCoCirc model which considers both ordering of sentences and interaction of words in composing text meaning from word and sentence meanings. DisCoCirc makes fundamental modification of DisCoCat since a sentence in DisCoCirc updates meanings of words, whereas all meanings are static in DisCoCat. It is not clear if DisCoCirc can be implemented in lambeq / DisCoCat without breaking DisCoCat.
Abstract (translated)
作为最近在量子自然语言处理(QNLP)研究中的一支努力,我们在 Lambeq / DisCoPy 中实现了 variational 量子句子分类器(VQSCs),基于句子意义的 DisCoCat 模型。我们详细讨论了 VQSCs,包括分类理论、将句子建模为字符串Diagram的 DisCoCat 以及将字符串Diagram编码为参数化的量子电路的 DisCoPy。然而,许多 NLP 任务需要处理包含多个句子的文本,这在 Lambeq / DisCoPy 中不支持。一个良好的例子是情感分类 customer 反馈或产品评论。我们讨论了三种与 VQSCs 相关的可能方法。第一种是加权句子包方法,将文本视为具有任务特定句子权重的独立句子群,第二种是共指关系解决方法,将文本视为其成员句子的整合,并解决它们之间的共指关系。这两种方法都基于 DisCoCat 模型,应该在 Lambeq / DisCoPy 中实现。第三种方法是基于 DisCocirc 模型,它考虑句子的排序和单词之间的交互,以从单词和句子意义构建文本意义。DisCocirc 对 DisCoCat 进行了基本修改,因为在一个 DisCocirc 句子中,单词的意义更新了,而在 DisCoCat 中,所有意义都是静态的。目前还不清楚,是否可以在 Lambeq / DisCoPy 中实现 DisCocirc,而不必破坏 DisCoCat。
URL
https://arxiv.org/abs/2303.02469
