3 accepted papers
Few-shot Multi-label Aspect Category Detection (FMACD) is an essential task, which aims to identify multiple aspect categories in a given sentence with limited data. Recently, the prototypical network as a mainline has been used for the task due to its powerful capacity. However, existing methods mo…
Image-enhanced knowledge graph completion aims to predict potential linkings in KGs by utilizing auxiliary visual information from entity’s images. Ideally, the image selection process should be dynamic, considering the context of inferred relations. However, current methods often assess image impor…
Deep learning models for automatic readability assessment generally discard linguistic features traditionally used in machine learning models for the task. We propose to incorporate linguistic features into neural network models by learning syntactic dense embeddings based on linguistic features. To…