The Importance of the Current Input in Sequence Modeling

22 December 2021

Papers citing "The Importance of the Current Input in Sequence Modeling"

14 / 14 papers shown

Title
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 743 41,932 0 28 May 2020
Separation of Memory and Processing in Dual Recurrent Neural Networks Christian Oliva Luis F. Lago-Fernández 36 1 0 17 May 2020
Improving Neural Language Modeling via Adversarial Training Dilin Wang Chengyue Gong Qiang Liu AAML 75 118 0 10 Jun 2019
FRAGE: Frequency-Agnostic Word Representation Chengyue Gong Di He Xu Tan Tao Qin Liwei Wang Tie-Yan Liu OOD 59 144 0 18 Sep 2018
Direct Output Connection for a High-Rank Language Model Sho Takase Jun Suzuki Masaaki Nagata 65 36 0 30 Aug 2018
Improved Language Modeling by Decoding the Past Siddhartha Brahma BDL AI4TS 37 6 0 14 Aug 2018
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model Zhilin Yang Zihang Dai Ruslan Salakhutdinov William W. Cohen BDL 66 371 0 10 Nov 2017
Dynamic Evaluation of Neural Sequence Models Ben Krause Emmanuel Kahembwe Iain Murray Steve Renals 62 134 0 21 Sep 2017
Regularizing and Optimizing LSTM Language Models Stephen Merity N. Keskar R. Socher 163 1,095 0 07 Aug 2017
Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling Hakan Inan Khashayar Khosravi R. Socher 108 384 0 04 Nov 2016
Pointer Sentinel Mixture Models Stephen Merity Caiming Xiong James Bradbury R. Socher RALM 308 2,859 0 26 Sep 2016
Using the Output Embedding to Improve Language Models Ofir Press Lior Wolf 69 733 0 20 Aug 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,039 0 22 Dec 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 1.0K 23,344 0 03 Jun 2014