b'Di Jin'

research

∙ 05/25/2022

TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature

Trust evaluation is critical for many applications such as cyber securit...

Cuiying Huo, et al. ∙

research

∙ 05/18/2022

On the Limits of Evaluating Embodied Agent Model Generalization Using Validation Sets

Natural language guided embodied task completion is a challenging proble...

Hyounghun Kim, et al. ∙

research

∙ 04/30/2022

Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning

Heterogeneous graph neural network (HGNN) is a very popular technique fo...

Di Jin, et al. ∙

research

∙ 03/17/2022

TMS: A Temporal Multi-scale Backbone Design for Speaker Embedding

Speaker embedding is an important front-end module to explore discrimina...

Ruiteng Zhang, et al. ∙

research

∙ 02/14/2022

Graph Neural Networks for Graphs with Heterophily: A Survey

Recent years have witnessed fast developments of graph neural networks (...

Xin Zheng, et al. ∙

research

∙ 12/05/2021

Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View

The increasing availability of large collections of electronic health re...

Di Jin, et al. ∙

research

∙ 11/09/2021

Convolutional Neural Network Dynamics: A Graph Perspective

The success of neural networks (NNs) in a wide range of applications has...

Fatemeh Vahedian, et al. ∙

research

∙ 10/27/2021

Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation

Multi-source entity linkage focuses on integrating knowledge from multip...

Di Jin, et al. ∙

research

∙ 06/16/2021

Can I Be of Further Assistance? Using Unstructured Knowledge Access to Improve Task-oriented Conversational Modeling

Most prior work on task-oriented dialogue systems are restricted to limi...

Di Jin, et al. ∙

research

∙ 01/31/2021

Adversarial Contrastive Pre-training for Protein Sequences

Recent developments in Natural Language Processing (NLP) demonstrate tha...

Matthew B. A. McDermott, et al. ∙

research

∙ 01/13/2021

Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search

Result relevance prediction is an essential task of e-commerce search en...

Ziyang Liu, et al. ∙

research

∙ 01/03/2021

A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning

Community detection, a fundamental task for network analysis, aims to pa...

Di Jin, et al. ∙

research

∙ 11/01/2020

Deep Learning for Text Attribute Transfer: A Survey

Driven by the increasingly larger deep learning models, neural language ...

Di Jin, et al. ∙

research

∙ 10/23/2020

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...

Di Jin, et al. ∙

research

∙ 10/22/2020

Graph Neural Network for Large-Scale Network Localization

Graph neural networks (GNNs) are popular to use for classifying structur...

Wenzhong Yan, et al. ∙

research

∙ 10/20/2020

BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search

Relevance has significant impact on user experience and business profit ...

Yunjiang Jiang, et al. ∙

research

∙ 09/28/2020

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...

Di Jin, et al. ∙

research

∙ 09/21/2020

From Static to Dynamic Node Embeddings

We introduce a general framework for leveraging graph stream data for te...

Di Jin, et al. ∙

research

∙ 09/16/2020

Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) aims to predict the sentiment tow...

Xiaoyu Xing, et al. ∙

research

∙ 08/06/2020

Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards

Generating accurate descriptions for online fashion items is important n...

Xuewen Yang, et al. ∙

research

∙ 07/14/2020

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...

Yaman Kumar, et al. ∙

research

∙ 07/06/2020

GCN for HIN via Implicit Utilization of Attention and Meta-paths

Heterogeneous information network (HIN) embedding, aiming to map the str...

Di Jin, et al. ∙

research

∙ 06/11/2020

Learning Continuous-Time Dynamics by Stochastic Differential Networks

Learning continuous-time stochastic dynamics from sparse or irregular ob...

Yingru Liu, et al. ∙

research

∙ 04/13/2020

From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap

Dialogue state tracking (DST) is at the heart of task-oriented dialogue ...

Shuyang Gao, et al. ∙

research

∙ 04/04/2020

Hooks in the Headline: Learning to Generate Headlines with Controlled Styles

Current summarization systems only produce plain, factual headlines, but...

Di Jin, et al. ∙

research

∙ 01/22/2020

Unsupervised Domain Adaptation for Neural Machine Translation with Iterative Back Translation

State-of-the-art neural machine translation (NMT) systems are data-hungr...

Di Jin, et al. ∙

research

∙ 10/01/2019

MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension

Machine Reading Comprehension (MRC) for question answering (QA), which a...

Di Jin, et al. ∙

research

∙ 08/22/2019

From Community to Role-based Graph Embeddings

Roles are sets of structurally similar nodes that are more similar to no...

Ryan A. Rossi, et al. ∙

research

∙ 07/27/2019

Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment

Machine learning algorithms are often vulnerable to adversarial examples...

Di Jin, et al. ∙

research

∙ 04/18/2019

node2bits: Compact Time- and Attribute-aware Node Representations for User Stitching

Identity stitching, the task of identifying and matching various online ...

Di Jin, et al. ∙

research

∙ 04/06/2019

Publicly Available Clinical BERT Embeddings

Contextual word embedding models such as ELMo (Peters et al., 2018) and ...

Emily Alsentzer, et al. ∙

research

∙ 01/31/2019

Unsupervised Text Style Transfer via Iterative Matching and Translation

Text style transfer seeks to learn how to automatically rewrite sentence...

Zhijing Jin, et al. ∙

research

∙ 10/30/2018

Advancing PICO Element Detection in Medical Text via Deep Neural Networks

In evidence-based medicine (EBM), structured medical questions are alway...

Di Jin, et al. ∙

research

∙ 08/19/2018

Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts

Prevalent models based on artificial neural network (ANN) for sentence c...

Di Jin, et al. ∙

research

∙ 01/07/2018

High-throughput, high-resolution Generated Adversarial Network Microscopy

We for the first time combine generated adversarial network (GAN) with w...

Hao Zhang, et al. ∙

Di Jin

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