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Parsing as Language Modeling
Do Kook Choe
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Eugene Charniak
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Paper Details:
Month: November
Year: 2016
Location: Austin, Texas
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Two Local Models for Neural Constituent Parsing
Zhiyang Teng
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Yue Zhang
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Fast(er) Exact Decoding and Global Training for Transition-Based Dependency Parsing via a Minimal Feature Set
Tianze Shi
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Liang Huang
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Lillian Lee
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Word-Context Character Embeddings for Chinese Word Segmentation
Hao Zhou
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Zhenting Yu
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Yue Zhang
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Shujian Huang
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Xinyu Dai
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Jiajun Chen
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Effective Inference for Generative Neural Parsing
Mitchell Stern
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Daniel Fried
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Dan Klein
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A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
Kazuma Hashimoto
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Caiming Xiong
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Yoshimasa Tsuruoka
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Richard Socher
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Top-down Tree Structured Decoding with Syntactic Connections for Neural Machine Translation and Parsing
Jetic Gū
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Hassan S. Shavarani
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Anoop Sarkar
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Constituent Parsing as Sequence Labeling
Carlos Gómez-Rodríguez
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David Vilares
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Cross-lingual Decompositional Semantic Parsing
Sheng Zhang
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Xutai Ma
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Rachel Rudinger
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Kevin Duh
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Benjamin Van Durme
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Improved Dependency Parsing using Implicit Word Connections Learned from Unlabeled Data
Wenhui Wang
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Baobao Chang
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Mairgup Mansur
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Multi-Source Syntactic Neural Machine Translation
Anna Currey
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Kenneth Heafield
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Direct Output Connection for a High-Rank Language Model
Sho Takase
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Jun Suzuki
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Masaaki Nagata
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What Do Recurrent Neural Network Grammars Learn About Syntax?
Adhiguna Kuncoro
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Miguel Ballesteros
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Lingpeng Kong
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Chris Dyer
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Graham Neubig
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Noah A. Smith
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MT/IE: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models
Sheng Zhang
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Kevin Duh
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Benjamin Van Durme
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K-best Iterative Viterbi Parsing
Katsuhiko Hayashi
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Masaaki Nagata
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An Improved Neural Network Model for Joint POS Tagging and Dependency Parsing
Dat Quoc Nguyen
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Karin Verspoor
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What’s Going On in Neural Constituency Parsers? An Analysis
David Gaddy
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Mitchell Stern
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Dan Klein
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Learning Structured Natural Language Representations for Semantic Parsing
Jianpeng Cheng
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Siva Reddy
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Vijay Saraswat
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Mirella Lapata
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Deep Semantic Role Labeling: What Works and What’s Next
Luheng He
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Kenton Lee
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Mike Lewis
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Luke Zettlemoyer
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Modeling Source Syntax for Neural Machine Translation
Junhui Li
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Deyi Xiong
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Zhaopeng Tu
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Muhua Zhu
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Min Zhang
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Guodong Zhou
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Towards String-To-Tree Neural Machine Translation
Roee Aharoni
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Yoav Goldberg
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Improving Neural Parsing by Disentangling Model Combination and Reranking Effects
Daniel Fried
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Mitchell Stern
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Dan Klein
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LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better
Adhiguna Kuncoro
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Chris Dyer
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John Hale
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Dani Yogatama
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Stephen Clark
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Phil Blunsom
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Constituency Parsing with a Self-Attentive Encoder
Nikita Kitaev
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Dan Klein
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Finding syntax in human encephalography with beam search
John Hale
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Chris Dyer
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Adhiguna Kuncoro
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Jonathan Brennan
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Policy Gradient as a Proxy for Dynamic Oracles in Constituency Parsing
Daniel Fried
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Dan Klein
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Linear-time Constituency Parsing with RNNs and Dynamic Programming
Juneki Hong
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Liang Huang
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An Empirical Study of Building a Strong Baseline for Constituency Parsing
Jun Suzuki
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Sho Takase
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Hidetaka Kamigaito
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Makoto Morishita
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Masaaki Nagata
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On the Practical Computational Power of Finite Precision RNNs for Language Recognition
Gail Weiss
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Yoav Goldberg
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Eran Yahav
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Head-Lexicalized Bidirectional Tree LSTMs
Zhiyang Teng
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Yue Zhang
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In-Order Transition-based Constituent Parsing
Jiangming Liu
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Yue Zhang
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Encoder-Decoder Shift-Reduce Syntactic Parsing
Jiangming Liu
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Yue Zhang
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Arc-Standard Spinal Parsing with Stack-LSTMs
Miguel Ballesteros
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Xavier Carreras
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No URLs Found
Field Of Study
Linguistic Trends
Embeddings
Task
Syntactic Parsing
Machine Translation
Approach
Deep Learning
Discriminative Model
Language
English
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