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Paired Representation Learning for Event and Entity Coreference
Co-reference of Events and of Entities are commonly formulated as binary...
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Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start
A standard way to address different NLP problems is by first constructin...
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Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks
Mixup is the latest data augmentation technique that linearly interpolat...
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Meta-learning for Few-shot Natural Language Processing: A Survey
Few-shot natural language processing (NLP) refers to NLP tasks that are ...
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CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization
The COVID-19 global pandemic has resulted in international efforts to un...
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Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT
There is an increasing amount of literature that claims the brittleness ...
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Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
Zero-shot text classification (0Shot-TC) is a challenging NLU problem to...
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An Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
Multi-Task Learning (MTL) aims at boosting the overall performance of ea...
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Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims
One key consequence of the information revolution is a significant incre...
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TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification
Determining whether a given claim is supported by evidence is a fundamen...
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Term Definitions Help Hypernymy Detection
Existing methods of hypernymy detection mainly rely on statistics over a...
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Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs
Large scale knowledge graphs (KGs) such as Freebase are generally incomp...
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End-Task Oriented Textual Entailment via Deep Explorations of Inter-Sentence Interactions
This work deals with SciTail, a natural entailment challenge derived fro...
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End-Task Oriented Textual Entailment via Deep Exploring Inter-Sentence Interactions
This work deals with SciTail, a natural entailment problem derived from ...
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Attentive Convolution
In NLP, convolution neural networks (CNNs) have benefited less than recu...
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Improved Neural Relation Detection for Knowledge Base Question Answering
Relation detection is a core component for many NLP applications includi...
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Comparative Study of CNN and RNN for Natural Language Processing
Deep neural networks (DNN) have revolutionized the field of natural lang...
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Task-Specific Attentive Pooling of Phrase Alignments Contributes to Sentence Matching
This work studies comparatively two typical sentence matching tasks: tex...
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Simple Question Answering by Attentive Convolutional Neural Network
This work focuses on answering single-relation factoid questions over Fr...
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Why and How to Pay Different Attention to Phrase Alignments of Different Intensities
This work studies comparatively two typical sentence pair classification...
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Discriminative Phrase Embedding for Paraphrase Identification
This work, concerning paraphrase identification task, on one hand contri...
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Online Updating of Word Representations for Part-of-Speech Tagging
We propose online unsupervised domain adaptation (DA), which is performe...
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Multichannel Variable-Size Convolution for Sentence Classification
We propose MVCNN, a convolution neural network (CNN) architecture for se...
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Attention-Based Convolutional Neural Network for Machine Comprehension
Understanding open-domain text is one of the primary challenges in natur...
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ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
How to model a pair of sentences is a critical issue in many NLP tasks s...
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Learning Meta-Embeddings by Using Ensembles of Embedding Sets
Word embeddings -- distributed representations of words -- in deep learn...
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