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Distribution System Voltage Prediction from Smart Inverters using Decentralized Regression
As photovoltaic (PV) penetration continues to rise and smart inverter fu...
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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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An Enhanced Knowledge Injection Model for Commonsense Generation
Commonsense generation aims at generating plausible everyday scenario de...
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ProphetNet-Ads: A Looking Ahead Strategy for Generative Retrieval Models in Sponsored Search Engine
In a sponsored search engine, generative retrieval models are recently p...
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Neural Deepfake Detection with Factual Structure of Text
Deepfake detection, the task of automatically discriminating machine-gen...
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Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous Space
In this paper, we propose a novel data augmentation method, referred to ...
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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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GraphCodeBERT: Pre-training Code Representations with Data Flow
Pre-trained models for programming language have achieved dramatic empir...
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Tag and Correct: Question aware Open Information Extraction with Two-stage Decoding
Question Aware Open Information Extraction (Question aware Open IE) take...
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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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M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training
This paper presents a Multitask Multilingual Multimodal Pre-trained mode...
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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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A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos
Procedural knowledge, which we define as concrete information about the ...
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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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A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts
We study question answering over a dynamic textual environment. Although...
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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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XGPT: Cross-modal Generative Pre-Training for Image Captioning
While many BERT-based cross-modal pre-trained models produce excellent r...
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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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UniViLM: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
We propose UniViLM: a Unified Video and Language pre-training Model for ...
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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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ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training
In this paper, we present a new sequence-to-sequence pre-training model ...
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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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Reasoning Over Semantic-Level Graph for Fact Checking
We study fact-checking in this paper, which aims to verify a textual cla...
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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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A Tensorized Transformer for Language Modeling
Latest development of neural models has connected the encoder and decode...
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Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing
In this paper, we present an approach to incorporate retrieved datapoint...
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Deep Reason: A Strong Baseline for Real-World Visual Reasoning
This paper presents a strong baseline for real-world visual reasoning (G...
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PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph
Despite some exciting progress on high-quality image generation from str...
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Pretraining-Based Natural Language Generation for Text Summarization
In this paper, we propose a novel pretraining-based encoder-decoder fram...
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Knowledge-Aware Conversational Semantic Parsing Over Web Tables
Conversational semantic parsing over tables requires knowledge acquiring...
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Knowledge Based Machine Reading Comprehension
Machine reading comprehension (MRC) requires reasoning about both the kn...
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Improving Question Answering by Commonsense-Based Pre-Training
Although neural network approaches achieve remarkable success on a varie...
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Question Generation from SQL Queries Improves Neural Semantic Parsing
We study how to learn a semantic parser of state-of-the-art accuracy wit...
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Table-to-Text: Describing Table Region with Natural Language
In this paper, we present a generative model to generate a natural langu...
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R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering
Recently, Visual Question Answering (VQA) has emerged as one of the most...
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Semantic Parsing with Syntax- and Table-Aware SQL Generation
We present a generative model to map natural language questions into SQL...
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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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Visual Question Generation as Dual Task of Visual Question Answering
Recently visual question answering (VQA) and visual question generation ...
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Content-Based Table Retrieval for Web Queries
Understanding the connections between unstructured text and semi-structu...
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Question Answering and Question Generation as Dual Tasks
We study the problem of joint question answering (QA) and question gener...
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