Despite the success of language models using neural networks, it remains unclear to what
extent neural models have the generalization ability to perform inferences. In this paper, we …

摘要近年来, 随着深度神经网络的快速发展, 它在越来越多的领域中有了广泛的应用.
深度神经网络模型在处理有序列依赖关系的预测问题时, 需要利用之前学习到的信息进行记忆 …

Disinformation detection is emerging as an important research challenge due to the rise of
disinformation on digital platforms. Several methods have been proposed in the literature to …

Modeling sequential information for image sequences is a vital step of various vision tasks
and convolutional long short-term memory (ConvLSTM) has demonstrated its superb …

With the increase in misinformation across digital platforms, incongruent news detection is
becoming an important research problem. Earlier, researchers have exploited various …

This paper describes an approach to solve implicit emotion classification with the use of pre-
trained word embedding models to train multiple neural networks. The system described in …

[Objective] This paper constructs a clustering model for sentimental time series of bullet
screen texts, aiming to predict video communication effects.[Methods] First, we used the …

In many applications such as natural language processing, speech recognition, and
computer vision, there are inputs with hierarchical compositional structure and long relation …

Modeling the sequential information of image sequences has been a vital step of various
vision tasks and convolutional long short-term memory (ConvLSTM) has demonstrated its …

With the increasing scale of software and the growing number of software developers, code
cloning has become an important issue in software engineering. To detect code clones, this …