2 citations · 4 across the 5 of their papers we have counts for
5 papers
Syntax-guided Localized Self-attention by Constituency Syntactic Distance
Shengyuan Hou, Jushi Kai, Haotian Xue +5
Recent works have revealed that Transformers are implicitly learning the syntactic information in its lower layers from data, albeit is highly dependent on the quality and scale of…
Melody Infilling with User-Provided Structural Context
Chih-Pin Tan, Alvin W. Y. Su, Yi-Hsuan Yang
This paper proposes a novel Transformer-based model for music score infilling, to generate a music passage that fills in the gap between given past and future contexts. While exist…
INFINITY: A Simple Yet Effective Unsupervised Framework for Graph-Text Mutual Conversion
Yi Xu, Luoyi Fu, Zhouhan Lin +2
Graph-to-text (G2T) generation and text-to-graph (T2G) triple extraction are two essential tasks for constructing and applying knowledge graphs. Existing unsupervised approaches tu…
Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition
Xichen Pan, Peiyu Chen, Yichen Gong +3
Training Transformer-based models demands a large amount of data, while obtaining aligned and labelled data in multimodality is rather cost-demanding, especially for audio-visual s…
DeepShovel: An Online Collaborative Platform for Data Extraction in Geoscience Literature with AI Assistance
Shao Zhang, Yuting Jia, Hui Xu +3
Geoscientists, as well as researchers in many fields, need to read a huge amount of literature to locate, extract, and aggregate relevant results and data to enable future research…