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Adversarial Contrastive Pre-training for Protein Sequences
Recent developments in Natural Language Processing (NLP) demonstrate tha...
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Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search
Result relevance prediction is an essential task of e-commerce search en...
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A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
Community detection, a fundamental task for network analysis, aims to pa...
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Deep Learning for Text Attribute Transfer: A Survey
Driven by the increasingly larger deep learning models, neural language ...
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BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks
Graph convolutional networks (GCNs), aiming to integrate high-order neig...
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Graph Neural Network for Large-Scale Network Localization
Graph neural networks (GNNs) are popular to use for classifying structur...
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BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search
Relevance has significant impact on user experience and business profit ...
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What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Open domain question answering (OpenQA) tasks have been recently attract...
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From Static to Dynamic Node Embeddings
We introduce a general framework for leveraging graph stream data for te...
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Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) aims to predict the sentiment tow...
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Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards
Generating accurate descriptions for online fashion items is important n...
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Calling Out Bluff: Attacking the Robustness of Automatic Scoring Systems with Simple Adversarial Testing
A significant progress has been made in deep-learning based Automatic Es...
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GCN for HIN via Implicit Utilization of Attention and Meta-paths
Heterogeneous information network (HIN) embedding, aiming to map the str...
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Learning Continuous-Time Dynamics by Stochastic Differential Networks
Learning continuous-time stochastic dynamics from sparse or irregular ob...
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From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap
Dialogue state tracking (DST) is at the heart of task-oriented dialogue ...
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Hooks in the Headline: Learning to Generate Headlines with Controlled Styles
Current summarization systems only produce plain, factual headlines, but...
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Unsupervised Domain Adaptation for Neural Machine Translation with Iterative Back Translation
State-of-the-art neural machine translation (NMT) systems are data-hungr...
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MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension
Machine Reading Comprehension (MRC) for question answering (QA), which a...
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From Community to Role-based Graph Embeddings
Roles are sets of structurally similar nodes that are more similar to no...
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Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment
Machine learning algorithms are often vulnerable to adversarial examples...
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node2bits: Compact Time- and Attribute-aware Node Representations for User Stitching
Identity stitching, the task of identifying and matching various online ...
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Publicly Available Clinical BERT Embeddings
Contextual word embedding models such as ELMo (Peters et al., 2018) and ...
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Unsupervised Text Style Transfer via Iterative Matching and Translation
Text style transfer seeks to learn how to automatically rewrite sentence...
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Advancing PICO Element Detection in Medical Text via Deep Neural Networks
In evidence-based medicine (EBM), structured medical questions are alway...
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Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts
Prevalent models based on artificial neural network (ANN) for sentence c...
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High-throughput, high-resolution Generated Adversarial Network Microscopy
We for the first time combine generated adversarial network (GAN) with w...
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