On the Robustness of Self-Attentive Models. Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, and Cho-Jui Hsieh. ACL 2019. score [pdf] Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency. Shuhuai Ren, Yihe Deng, Kun He, Wanxiang Che...
astmt: Attentive Single-tasking of Multiple Tasks NLP ✨mt-dnn: Multi-Task Deep Neural Networks for Natural Language Understanding Recommendation System ✨MTReclib: MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets. ...
During the production of metal material, various complex defects may come into being on the surface, together with large amount of background texture information, causing false or missing detection in the process of small defect detection. To resolve those problems, this paper introduces a new mod...
During the manufacturing process of printed circuit boards (PCBs), quality defects can occur, which can affect the performance and reliability of PCBs. Existing deep learning-based PCB defect detection methods are difficult to simultaneously achieve the
initiative is part of a broader goal to achieve the development of self-driving vehicles and improve advanced driver assistance systems (ADAS). Autonomous driving technology is important for improving vehicle safety. In the past few years, with the advancement of deep learning architectures, the ...
Robustness Checks In addition, we also conduct other robustness checks in the Online Appendix B.2. First, we transform the disaster relief in a few different ways: the dummy variable of whether a municipality obtains any disaster relief in a year (Table B.3), the logarithm of the amount of...
Recent developments in Convolutional Neural Networks (ConvNets) have led to substantial progress in the performance of computer vision tasks applied across various domains such as self-driving cars [1], medical imaging [2], agriculture [3,4], manufacturing [5], etc. The availability of big data...
Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks. arxiv 2020. paper Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Chang-Tien Lu. Models Basic Models Supervised Neural Networks for the Classification of Structures...
Survey on the Use of Typological Information in Natural Language Processing. COLING 2016 paper bib Helen O'Horan, Yevgeni Berzak, Ivan Vulic, Roi Reichart, Anna Korhonen Machine Learning for NLP A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Represen...
A Structured Self-attentive Sentence Embedding Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, Yoshua Bengio ICLR 2018 Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering Daniil Sorokin, Iryna Gurevych COLING 2018 Exploiting...