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Found 9 papers, 3 papers with code
Multi-Granularity Semantic Aware Graph Model for Reducing Position Bias in Emotion Cause Pair Extraction
Besides, a clause graph is also established to model coarse-grained semantic relations between clauses.
Speaker-Guided Encoder-Decoder Framework for Emotion Recognition in Conversation
Since the dependencies between speakers are complex and dynamic, which consist of intra- and inter-speaker dependencies, the modeling of speaker-specific information is a vital role in ERC.
Multi-Granularity Semantic Aware Graph Model for Reducing Position Bias in Emotion-Cause Pair Extraction
Besides, a clause graph is also established to model coarse-grained semantic relations between clauses.
Label-Specific Dual Graph Neural Network for Multi-Label Text Classification
Multi-label text classification is one of the fundamental tasks in natural language processing.
SRLF: A Stance-aware Reinforcement Learning Framework for Content-based Rumor Detection on Social Media
The rapid development of social media changes the lifestyle of people and simultaneously provides an ideal place for publishing and disseminating rumors, which severely exacerbates social panic and triggers a crisis of social trust.
Early Detection of Fake News by Utilizing the Credibility of News, Publishers, and Users Based on Weakly Supervised Learning
In this way, we can explicitly exploit the credibility of publishers and users for early fake news detection.
Beyond Statistical Relations: Integrating Knowledge Relations into Style Correlations for Multi-Label Music Style Classification
Based on the two types of relations, we use a graph convolutional network to learn the deep correlations between styles automatically.
Learning review representations from user and product level information for spam detection
Then, we use orthogonal decomposition and fusion attention to learn a user, review, and product representation from the review information.
Jointly embedding the local and global relations of heterogeneous graph for rumor detection
The development of social media has revolutionized the way people communicate, share information and make decisions, but it also provides an ideal platform for publishing and spreading rumors.
