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Found 4 papers, 2 papers with code
JEPOO: Highly Accurate Joint Estimation of Pitch, Onset and Offset for Music Information Retrieval
In this paper, we propose a highly accurate method for joint estimation of pitch, onset and offset, named JEPOO.
Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus
In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.
Learning to Generate Questions by Learning What not to Generate
In CGC-QG, we design a multi-task labeling strategy to identify whether a question word should be copied from the input passage or be generated instead, guiding the model to learn the accurate boundaries between copying and generation.
Matching Article Pairs with Graphical Decomposition and Convolutions
Identifying the relationship between two articles, e. g., whether two articles published from different sources describe the same breaking news, is critical to many document understanding tasks.
