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Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing
We introduce Trankit, a light-weight Transformer-based Toolkit for multi...
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Acronym Identification and Disambiguation Shared Tasks for Scientific Document Understanding
Acronyms are the short forms of longer phrases and they are frequently u...
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Structural and Functional Decomposition for Personality Image Captioning in a Communication Game
Personality image captioning (PIC) aims to describe an image with a natu...
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What Does This Acronym Mean? Introducing a New Dataset for Acronym Identification and Disambiguation
Acronyms are the short forms of phrases that facilitate conveying length...
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Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks
Recent studies on event detection (ED) haveshown that the syntactic depe...
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Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction
The goal of Event Argument Extraction (EAE) is to find the role of each ...
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Improving Aspect-based Sentiment Analysis with Gated Graph Convolutional Networks and Syntax-based Regulation
Aspect-based Sentiment Analysis (ABSA) seeks to predict the sentiment po...
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Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning
Targeted opinion word extraction (TOWE) is a sub-task of aspect based se...
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Extensively Matching for Few-shot Learning Event Detection
Current event detection models under super-vised learning settings fail ...
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Exploiting the Matching Information in the Support Set for Few Shot Event Classification
The existing event classification (EC) work primarily focuseson the trad...
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Improving Slot Filling by Utilizing Contextual Information
Slot Filling is the task of extracting the semantic concept from a given...
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A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency
Definition Extraction (DE) is one of the well-known topics in Informatio...
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On the Effectiveness of the Pooling Methods for Biomedical Relation Extraction with Deep Learning
Deep learning models have achieved state-of-the-art performances on many...
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Extending Event Detection to New Types with Learning from Keywords
Traditional event detection classifies a word or a phrase in a given sen...
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Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control
Relation Extraction (RE) is one of the fundamental tasks in Information ...
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Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures
Event factuality prediction (EFP) is the task of assessing the degree to...
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One for All: Neural Joint Modeling of Entities and Events
The previous work for event extraction has mainly focused on the predict...
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Systematic Generalization: What Is Required and Can It Be Learned?
Numerous models for grounded language understanding have been recently p...
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BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop
Allowing humans to interactively train artificial agents to understand l...
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Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs
Finding names of people killed by police has become increasingly importa...
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A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing
Anti-phishing aims to detect phishing content/documents in a pool of tex...
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Toward Mention Detection Robustness with Recurrent Neural Networks
One of the key challenges in natural language processing (NLP) is to yie...
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Combining Neural Networks and Log-linear Models to Improve Relation Extraction
The last decade has witnessed the success of the traditional feature-bas...
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