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Semi-supervised sequence tagging with bidirectional language models
Matthew Peters
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Waleed Ammar
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Chandra Bhagavatula
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Russell Power
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Paper Details:
Month: July
Year: 2017
Location: Vancouver, Canada
Venue:
ACL |
Citations
URL
Contextual String Embeddings for Sequence Labeling
Alan Akbik
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Duncan Blythe
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Roland Vollgraf
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Design Challenges and Misconceptions in Neural Sequence Labeling
Jie Yang
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Shuailong Liang
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Yue Zhang
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Variational Sequential Labelers for Semi-Supervised Learning
Mingda Chen
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Qingming Tang
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Karen Livescu
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Kevin Gimpel
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Neural Cross-Lingual Named Entity Recognition with Minimal Resources
Jiateng Xie
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Zhilin Yang
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Graham Neubig
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Noah A. Smith
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Jaime Carbonell
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Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling
Liyuan Liu
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Xiang Ren
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Jingbo Shang
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Xiaotao Gu
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Jian Peng
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Jiawei Han
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Dissecting Contextual Word Embeddings: Architecture and Representation
Matthew Peters
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Mark Neumann
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Luke Zettlemoyer
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Wen-tau Yih
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Semi-Supervised Sequence Modeling with Cross-View Training
Kevin Clark
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Minh-Thang Luong
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Christopher D. Manning
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Quoc Le
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Neural Adaptation Layers for Cross-domain Named Entity Recognition
Bill Yuchen Lin
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Wei Lu
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Learning Better Internal Structure of Words for Sequence Labeling
Yingwei Xin
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Ethan Hart
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Vibhuti Mahajan
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Jean-David Ruvini
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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-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction
Yi Luan
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Luheng He
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Mari Ostendorf
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Hannaneh Hajishirzi
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Global Attention for Name Tagging
Boliang Zhang
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Spencer Whitehead
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Lifu Huang
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Heng Ji
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Model Transfer with Explicit Knowledge of the Relation between Class Definitions
Hiyori Yoshikawa
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Tomoya Iwakura
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Zero-Shot Sequence Labeling: Transferring Knowledge from Sentences to Tokens
Marek Rei
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Anders Søgaard
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Deep Contextualized Word Representations
Matthew Peters
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Mark Neumann
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Mohit Iyyer
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Matt Gardner
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Christopher Clark
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Kenton Lee
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Luke Zettlemoyer
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Construction of the Literature Graph in Semantic Scholar
Waleed Ammar
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Dirk Groeneveld
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Chandra Bhagavatula
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Iz Beltagy
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Miles Crawford
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Doug Downey
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Jason Dunkelberger
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Ahmed Elgohary
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Sergey Feldman
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Vu Ha
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Rodney Kinney
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Sebastian Kohlmeier
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Kyle Lo
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Tyler Murray
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Hsu-Han Ooi
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Matthew Peters
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Joanna Power
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Sam Skjonsberg
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Lucy Wang
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Chris Wilhelm
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Zheng Yuan
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Madeleine van Zuylen
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Oren Etzioni
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Sentence-State LSTM for Text Representation
Yue Zhang
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Qi Liu
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Linfeng Song
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Universal Language Model Fine-tuning for Text Classification
Jeremy Howard
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Sebastian Ruder
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Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search
Jamie Kiros
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William Chan
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Geoffrey Hinton
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Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples
Vidur Joshi
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Matthew Peters
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Mark Hopkins
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Chinese NER Using Lattice LSTM
Yue Zhang
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Jie Yang
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Hybrid semi-Markov CRF for Neural Sequence Labeling
Zhixiu Ye
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Zhen-Hua Ling
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Learning to Embed Words in Context for Syntactic Tasks
Lifu Tu
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Kevin Gimpel
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Karen Livescu
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NILC at CWI 2018: Exploring Feature Engineering and Feature Learning
Nathan Hartmann
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Leandro Borges dos Santos
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AllenNLP: A Deep Semantic Natural Language Processing Platform
Matt Gardner
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Joel Grus
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Mark Neumann
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Oyvind Tafjord
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Pradeep Dasigi
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Nelson F. Liu
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Matthew Peters
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Michael Schmitz
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Luke Zettlemoyer
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Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
Emma Strubell
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Andrew McCallum
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Connecting Supervised and Unsupervised Sentence Embeddings
Gil Levi
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Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.
Tuhin Chakrabarty
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Tariq Alhindi
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Smaranda Muresan
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https://doi.org/10.18653/v1/P17-1161
https://doi.org/10.18653/v1/P17-1161
https://github.com/tensorflow/models/
https://scienceie.github.io/
Field Of Study
Linguistic Trends
Embeddings
Syntax
Task
Tagging
Chunking
Word Sense Disambiguation
Named Entity Recognition
Relation Extraction
Machine Translation
Approach
Generative Model
Semi-supervised Learning
Language
Spanish
Dataset
News
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