摘要随着大规模预训练模型的广泛应用, 自然语言处理的多个领域(如文本分类和机器翻译)
取得了长足的发展. 然而, 受限于预训练模型的“黑盒” 特性, 其内部的决策模式以及编码的知识 …

We introduce Holmes, a new benchmark designed to assess language models'(LMs')
linguistic competence—their unconscious understanding of linguistic phenomena …

Large NLP models have recently shown impressive performance in language
understanding tasks, typically evaluated by their fine-tuned performance. Alternatively …

The impressive success of recent deep neural network (DNN)-based systems is significantly
influenced by the high-quality datasets used in training. However, the effects of the datasets …

The vast body of research is dedicated to interpreting language models, particularly probing
them for linguistic properties. As in many other NLP fields, probing works tend to reuse …

In recent years, the impressive abilities shown by deep neural network (DNN)-based
systems have led to the curiosity towards the intrinsic mechanisms. The query towards these …