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Syntax-Enhanced Pre-trained Model
We study the problem of leveraging the syntactic structure of text to en...
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Reinforced Multi-Teacher Selection for Knowledge Distillation
In natural language processing (NLP) tasks, slow inference speed and hug...
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CalibreNet: Calibration Networks for Multilingual Sequence Labeling
Lack of training data in low-resource languages presents huge challenges...
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Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation
Cross-lingual Machine Reading Comprehension (CLMRC) remains a challengin...
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A Graph Representation of Semi-structured Data for Web Question Answering
The abundant semi-structured data on the Web, such as HTML-based tables ...
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Towards Interpretable Reasoning over Paragraph Effects in Situation
We focus on the task of reasoning over paragraph effects in situation, w...
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Knowledge-Aware Procedural Text Understanding with Multi-Stage Training
We focus on the task of procedural text understanding, which aims to tra...
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No Answer is Better Than Wrong Answer: A Reflection Model for Document Level Machine Reading Comprehension
The Natural Questions (NQ) benchmark set brings new challenges to Machin...
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GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
In this paper, we focus on the imbalance issue, which is rarely studied ...
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Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation
In a multi-turn knowledge-grounded dialog, the difference between the kn...
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GraphCodeBERT: Pre-training Code Representations with Data Flow
Pre-trained models for programming language have achieved dramatic empir...
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Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder
Generating inferential texts about an event in different perspectives re...
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Mining Implicit Relevance Feedback from User Behavior for Web Question Answering
Training and refreshing a web-scale Question Answering (QA) system for a...
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Mining Implicit Relevance Feedback from User Behavior forWeb Question Answering
Training and refreshing a web-scale Question Answering (QA) system for a...
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Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension
Natural Questions is a new challenging machine reading comprehension ben...
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RikiNet: Reading Wikipedia Pages for Natural Question Answering
Reading long documents to answer open-domain questions remains challengi...
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Leveraging Declarative Knowledge in Text and First-Order Logic for Fine-Grained Propaganda Detection
We study the detection of propagandistic text fragments in news articles...
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Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension
Multilingual pre-trained models could leverage the training data from a ...
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LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network
Verifying the correctness of a textual statement requires not only seman...
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Pre-training Text Representations as Meta Learning
Pre-training text representations has recently been shown to significant...
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Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation
News headline generation aims to produce a short sentence to attract rea...
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Inferential Text Generation with Multiple Knowledge Sources and Meta-Learning
We study the problem of generating inferential texts of events for a var...
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XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
In this paper, we introduce XGLUE, a new benchmark dataset to train larg...
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DC-BERT: Decoupling Question and Document for Efficient Contextual Encoding
Recent studies on open-domain question answering have achieved prominent...
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CodeBERT: A Pre-Trained Model for Programming and Natural Languages
We present CodeBERT, a bimodal pre-trained model for programming languag...
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K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
We study the problem of injecting knowledge into large pre-trained model...
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Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System
Deep pre-training and fine-tuning models (such as BERT and OpenAI GPT) h...
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Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base
We consider the problem of conversational question answering over a larg...
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Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning
Neural semantic parsing has achieved impressive results in recent years,...
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Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
Commonsense question answering aims to answer questions which require ba...
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Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering
Many algorithms for Knowledge-Based Question Answering (KBQA) depend on ...
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Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks
We present Unicoder, a universal language encoder that is insensitive to...
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Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training
We propose Unicoder-VL, a universal encoder that aims to learn joint rep...
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Model Compression with Multi-Task Knowledge Distillation for Web-scale Question Answering System
Deep pre-training and fine-tuning models (like BERT, OpenAI GPT) have de...
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NeuronBlocks -- Building Your NLP DNN Models Like Playing Lego
When building deep neural network models for natural language processing...
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Assertion-based QA with Question-Aware Open Information Extraction
We present assertion based question answering (ABQA), an open domain que...
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