Name
Affiliation
Papers
KEWEI TU
Department of Computer Science and Engineering, Shanghai JiaoTong University, Shanghai, P.R.China
62
Collaborators
Citations 
PageRank 
104
136
25.00
Referers 
Referees 
References 
350
852
404
Search Limit
100852
Title
Citations
PageRank
Year
SHARP: Search-Based Adversarial Attack for Structured Prediction.00.342022
Span-Based Semantic Role Labeling with Argument Pruning and Second-Order Inference.00.342022
Combining (Second-Order) Graph-Based and Headed-Span-Based Projective Dependency Parsing00.342022
Headed-Span-Based Projective Dependency Parsing00.342022
ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition00.342022
Unsupervised Natural Language Parsing (Introductory Tutorial).00.342021
Neuralizing Regular Expressions for Slot Filling.00.342021
Generalized Supervised Attention for Text Generation.00.342021
PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols00.342021
Unsupervised Cross-Lingual Adaptation of Dependency Parsers Using CRF Autoencoders.00.342020
AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network.00.342020
An Empirical Study Of Encoders And Decoders In Graph-Based Dependency Parsing00.342020
Semi-Supervised Semantic Dependency Parsing Using CRF Autoencoders00.342020
An Investigation of Potential Function Designs for Neural CRF00.342020
Cold-Start and Interpretability: Turning Regular Expressions into Trainable Recurrent Neural Networks.00.342020
More Embeddings, Better Sequence Labelers?00.342020
A Survey of Unsupervised Dependency Parsing00.342020
Second-Order Unsupervised Neural Dependency Parsing00.342020
Second-Order Neural Dependency Parsing with Message Passing and End-to-End Training00.342020
Deep Inside-outside Recursive Autoencoder with All-span Objective.00.342020
Enhanced Universal Dependency Parsing With Second-Order Inference And Mixture Of Training Data00.342020
Adversarial Attack and Defense of Structured Prediction Models.00.342020
Learning Numeral Embedding.00.342020
Semi-Supervised Dependency Parsing with Arc-Factored Variational Autoencoding.00.342020
Bidirectional Transition-Based Dependency Parsing00.342019
ShanghaiTech at MRP 2019 - Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing.00.342019
Latent Variable Autoencoder.00.342019
Enhancing Unsupervised Generative Dependency Parser with Contextual Information00.342019
A Regularization-based Framework for Bilingual Grammar Induction00.342019
Learning and evaluation of latent dependency forest models00.342019
Multilingual Grammar Induction with Continuous Language Identification00.342019
Lexicalized Neural Unsupervised Dependency Parsing.00.342019
Projective Latent Dependency Forest Models00.342019
QA4IE: A Question Answering based Framework for Information Extraction.20.362018
Gaussian Mixture Latent Vector Grammars00.342018
Maximum A Posteriori Inference in Sum-Product Networks00.342018
Gaussian Mixture Latent Vector Grammars.00.342018
Language Style Transfer from Sentences with Arbitrary Unknown Styles.10.352018
Learning Bayesian network structures under incremental construction curricula.20.372017
Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition.00.342017
Dependency Grammar Induction with Neural Lexicalization and Big Training Data.10.352017
Latent Dependency Forest Models.10.352017
Semi-supervised Structured Prediction with Neural CRF Autoencoder.30.382017
CRF Autoencoder for Unsupervised Dependency Parsing.30.372017
Modified Dirichlet Distribution: Allowing Negative Parameters to Induce Stronger Sparsity.00.342016
Unsupervised Neural Dependency Parsing.20.362016
Context-Dependent Sense Embedding.20.352016
Sequence Prediction Using Neural Network Classiers.00.342016
Stochastic And-Or Grammars: A Unified Framework and Logic Perspective00.342015
Curriculum Learning of Bayesian Network Structures.20.372015
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