5 accepted papers
Machine Reading Comprehension (MRC) reveals the ability to understand a given text passage and answer questions based on it. Existing research works in MRC rely heavily on large-size models and corpus to improve the performance evaluated by metrics such as Exact Match (EM) and F1. However, such a pa…
Contrastive Learning has emerged as a powerful representation learning method and facilitates various downstream tasks especially when supervised data is limited. How to construct efficient contrastive samples through data augmentation is key to its success. Unlike vision tasks, the data augmentatio…
The task of Grounded Video Description~(GVD) is to generate sentences whose objects can be grounded with the bounding boxes in the video frames. Existing works often fail to exploit structural information both in modeling the relationships among the region proposals and in attending them for text ge…
The task of RDF-to-text generation is to generate a corresponding descriptive text given a set of RDF triples. Most of the previous approaches either cast this task as a sequence-to-sequence problem or employ graph-based encoder for modeling RDF triples and decode a text sequence. However, none of t…
Time series data analytics has been a problem of substantial interests for decades, and Dynamic Time Warping (DTW) has been the most widely adopted technique to measure dissimilarity between time series. A number of global-alignment kernels have since been proposed in the spirit of DTW to extend its…