Search Options
| About 167,000 results Learning to Skim Texthttps://arxiv.org/abs/1704.06877 - Cached Apr 23, 2017 ... Authors: Adams Wei Yu, Hongrae Lee, Quoc V. Le ... In this paper, we present an approach of reading text while skipping irrelevant information if needed. The underlying model is a recurrent network that learns how far to jump after reading a few words of the input text. ... From: Adams Wei Yu [view email] [PDF] Learning to Skim Text - Carnegie Mellon School of Computer Sciencewww.cs.cmu.edu/~weiyu/Adams_Wei_Yu...files/acl17cr.pdf - Cached Learning to Skim Text. Adams Wei Yu∗. Carnegie Mellon University weiyu@cs.cmu.edu. Hongrae Lee. Google hrlee@google.com. Quoc V. Le. Google. Thanapon Noraset | Learning to Skim Texthttps://northanapon.github.io/papers/.../lang-to-program-rl-mml.html - Cached Learning to Skim Text. Adams Wei Yu, Hongrae Lee, Quoc V. Le [article]. 08 May 2017. Nor's personal website. with the help of these awesome open sources: ... Learning to Skim Text - ResearchGatehttps://www.researchgate.net/.../316451383_Learning_to_Skim_Text May 14, 2017 ... Learning to Skim Text on ResearchGate, the professional network for ... of the structured prediction problem (Li et al., 2016;Yu et al., 2017). Google Brain Publications - Real AIrealai.org/labs/google-brain/publications/ - Cached Learning and Evaluating Musical Features with Deep Autoencoders. ... 2017 April 23, Adams Wei Yu, Hongrae Lee, and Quoc V. Le. Learning to Skim Text. dblp: Hongrae Leedblp.uni-trier.de/pers/l/Lee:Hongrae - Cached List of computer science publications by Hongrae Lee. ... Adams Wei Yu, Hongrae Lee, Quoc V. Le: Learning to Skim Text. CoRR abs/1704.06877 (2017). [r1]. The Goldilocks Principle - Semantic Scholarhttps://www.semanticscholar.org/.../ Interestingly, we find that the amount of text encoded in a single memory ... Learning to Skim Text · Adams Wei Yu, Hongrae Lee, Quoc V. Le; ArXiv; 2017. 《Learning to Skim Text》A W Yu, H Lee, ... 来自爱可可-爱生活- 微博weibo.com/1402400261/F2yrbbZRu - Cached 《Learning to Skim Text》A W Yu, H Lee, Q V. Le [CMU & Google] (2017) http://t.cn/RaxEVgA | ||