Machine reading comprehension (MRC) requires machines to read and answer questions
about a given text. This can be achieved through either predicting answers or extracting …

Research has demonstrated the continuous growth of Large Language Models (LLMs) to
adversarial attacks, which involve the crafted input samples that can deceive even well …

[目的] 提出基于RoBERTa-wwm 动态融合的实体识别模型, 提高中文电子病历实体识别效果.[
方法] 将预训练语言模型RoBERTa-wwm 各Transformer 层生成的语义表示进行动态融合后 …

[Objective] This paper proposes an entity recognition model based on RoBERTa-wwm
dynamic fusion, aiming to improve the entity identification of Chinese electronic medical …

In recent years, pre-trained language models such as BERT (Bidirectional Encoder
Representations from Transformers) have demonstrated exceptional performance across …

The texts of safety risks in eletrical work describe the safety risks involved and management
measures. The text records information on potential risks, risk levels, and preventive …

BERT, a groundbreaking large language model, has excelled in natural language
processing tasks such as question answering. Motivated by a desire to understand BERT's …

In recent years, pre-trained language models such as BERT (Bidirectional Encoder
Representations from Transformers) have demonstrated exceptional performance across …

针对基于预训练模型的命名实体识别方法仅使用了预训练模型最后一层隐状态,
忽略了各Transformer 层对应不同文本信息的问题, 提出一种预训练模型多层动态融合方法 …