Recursive Neural Networks Can Learn Logical Semantics

v1v2v3v4 (latest)

Recursive Neural Networks Can Learn Logical Semantics

6 June 2014

Samuel R. Bowman

Christopher Potts

Christopher D. Manning

ArXiv (abs)PDF HTML

Papers citing "Recursive Neural Networks Can Learn Logical Semantics"

11 / 11 papers shown

Title
Ontology Reasoning with Deep Neural Networks Patrick Hohenecker Thomas Lukasiewicz NAI 101 85 0 24 Aug 2018
Semantic Parsing: Syntactic assurance to target sentence using LSTM Encoder CFG-Decoder Fabiano Ferreira Luz Marcelo Finger 13 1 0 18 Jul 2018
Learned in Translation: Contextualized Word Vectors Bryan McCann James Bradbury Caiming Xiong R. Socher 131 910 0 01 Aug 2017
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks Rajarshi Das Arvind Neelakantan David Belanger Andrew McCallum NAI AI4CE LRM 100 271 0 05 Jul 2016
Building a Fine-Grained Entity Typing System Overnight for a New X (X = Language, Domain, Genre) Lifu Huang Jonathan May Xiaoman Pan Heng Ji 56 19 0 10 Mar 2016
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing A. Kumar Ozan Irsoy Peter Ondruska Mohit Iyyer James Bradbury Ishaan Gulrajani Victor Zhong Romain Paulus R. Socher 129 1,182 0 24 Jun 2015
Compositional Vector Space Models for Knowledge Base Completion Arvind Neelakantan Benjamin Roth Andrew McCallum BDL CoGe KELM 75 283 0 24 Apr 2015
When Are Tree Structures Necessary for Deep Learning of Representations? Jiwei Li Thang Luong Dan Jurafsky Eduard H. Hovy 111 227 0 28 Feb 2015
Towards a Model Theory for Distributed Representations R. Guha 87 22 0 21 Oct 2014
Learning to Execute Wojciech Zaremba Ilya Sutskever ODL 114 560 0 17 Oct 2014
Learning Distributed Word Representations for Natural Logic Reasoning Samuel R. Bowman Christopher Potts Christopher D. Manning NAI 75 32 0 15 Oct 2014