Papers
Rethinking the Value of Network Pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou et al.
Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective
Kai Li, Martin Renqiang Min, Yun Fu
Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples
Jake Zhao (Junbo), Kyunghyun Cho
Retrieval-Enhanced Adversarial Training for Neural Response Generation
Qingfu Zhu, Lei Cui, Wei-Nan Zhang et al.
Retrieval-guided Dialogue Response Generation via a Matching-to-Generation Framework
Deng Cai, Yan Wang, Wei Bi et al.
Retrieval-guided Dialogue Response Generation via a Matching-to-Generation Framework
Deng Cai, Yan Wang, Wei Bi et al.
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
Minghao Hu, Yuxing Peng, Zhen Huang et al.
Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation
Chenze Shao, Yang Feng, Jinchao Zhang et al.
Retrofitting Contextualized Word Embeddings with Paraphrases
Weijia Shi, Muhao Chen, Pei Zhou et al.
Retrofitting Contextualized Word Embeddings with Paraphrases
Weijia Shi, Muhao Chen, Pei Zhou et al.
Retrosynthesis Prediction with Conditional Graph Logic Network
Hanjun Dai, Chengtao Li, Connor Coley et al.
Revealing and Predicting Online Persuasion Strategy with Elementary Units
Gaku Morio, Ryo Egawa, Katsuhide Fujita
Revealing and Predicting Online Persuasion Strategy with Elementary Units
Gaku Morio, Ryo Egawa, Katsuhide Fujita
Revealing interpretable object representations from human behavior
Charles Y. Zheng, Francisco Pereira, Chris I. Baker et al.
Revealing Scenes by Inverting Structure From Motion Reconstructions
Francesco Pittaluga, Sanjeev J. Koppal, Sing Bing Kang et al.
Revealing Semantic Structures of Texts: Multi-grained Framework for Automatic Mind-map Generation
Yang Wei, Honglei Guo, Jinmao Wei et al.
Revealing the Dark Secrets of BERT
Olga Kovaleva, Alexey Romanov, Anna Rogers et al.
Revealing the Dark Secrets of BERT
Olga Kovaleva, Alexey Romanov, Anna Rogers et al.
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
Yixin Nie, Songhe Wang, Mohit Bansal
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
Yixin Nie, Songhe Wang, Mohit Bansal
Revenue Enhancement via Asymmetric Signaling in Interdependent-Value Auctions
Zhuoshu Li, Sanmay Das
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
Niru Maheswaranathan, Alex Williams, Matthew Golub et al.
Reverse-Engineering Satire, or “Paper on Computational Humor Accepted despite Making Serious Advances”
Robert West, Eric Horvitz
“Reverse Gerrymandering”: Manipulation in Multi-Group Decision Making
Omer Lev, Yoad Lewenberg
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
Andrey Malinin, Mark Gales