b'Yujing Wang'

research

∙ 08/17/2023

Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning

Graph Active Learning (GAL), which aims to find the most informative nod...

0 Tianmeng Yang, et al. ∙

research

∙ 06/26/2023

Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference

Deploying pre-trained transformer models like BERT on downstream tasks i...

0 Junyan Li, et al. ∙

research

∙ 05/23/2023

To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion

Embedding models have shown great power in knowledge graph completion (K...

0 Rui Li, et al. ∙

research

∙ 03/17/2023

IRGen: Generative Modeling for Image Retrieval

While generative modeling has been ubiquitous in natural language proces...

0 Yidan Zhang, et al. ∙

research

∙ 03/15/2023

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Large Language Models (LLMs) are popular for their impressive abilities,...

0 Daixuan Cheng, et al. ∙

research

∙ 03/15/2023

SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference

The combination of Neural Architecture Search (NAS) and quantization has...

0 Li Lyna Zhang, et al. ∙

research

∙ 03/04/2023

Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders

Causal analysis for time series data, in particular estimating individua...

0 Defu Cao, et al. ∙

research

∙ 12/30/2022

Label-Efficient Interactive Time-Series Anomaly Detection

Time-series anomaly detection is an important task and has been widely a...

0 Hong Guo, et al. ∙

research

∙ 12/16/2022

Convolution-enhanced Evolving Attention Networks

Attention-based neural networks, such as Transformers, have become ubiqu...

0 Yujing Wang, et al. ∙

research

∙ 08/30/2022

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance

Ad relevance modeling plays a critical role in online advertising system...

6 Li Lyna Zhang, et al. ∙

research

∙ 08/02/2022

Binary Classification with Positive Labeling Sources

To create a large amount of training labels for machine learning models ...

0 Jieyu Zhang, et al. ∙

research

∙ 06/06/2022

A Neural Corpus Indexer for Document Retrieval

Current state-of-the-art document retrieval solutions mainly follow an i...

1 Yujing Wang, et al. ∙

research

∙ 04/12/2022

Stylized Knowledge-Grounded Dialogue Generation via Disentangled Template Rewriting

Current Knowledge-Grounded Dialogue Generation (KDG) models specialize i...

0 Qingfeng Sun, et al. ∙

research

∙ 10/16/2021

Multimodal Dialogue Response Generation

Responsing with image has been recognized as an important capability for...

20 Qingfeng Sun, et al. ∙

research

∙ 10/07/2021

Creating Training Sets via Weak Indirect Supervision

Creating labeled training sets has become one of the major roadblocks in...

9 Jieyu Zhang, et al. ∙

research

∙ 10/03/2021

Graph Pointer Neural Networks

Graph Neural Networks (GNNs) have shown advantages in various graph-base...

0 Tianmeng Yang, et al. ∙

research

∙ 09/23/2021

WRENCH: A Comprehensive Benchmark for Weak Supervision

Recent Weak Supervision (WS) approaches have had widespread success in e...

0 Jieyu Zhang, et al. ∙

research

∙ 09/05/2021

Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Recommendation

To alleviate data sparsity and cold-start problems of traditional recomm...

13 Yankai Chen, et al. ∙

research

∙ 06/21/2021

Graph Attention Networks with LSTM-based Path Reweighting

Graph Neural Networks (GNNs) have been extensively used for mining graph...

0 Jianpeng Chen, et al. ∙

research

∙ 06/19/2021

Learning Timestamp-Level Representations for Time Series with Hierarchical Contrastive Loss

This paper presents TS2Vec, a universal framework for learning timestamp...

0 Zhihan Yue, et al. ∙

research

∙ 03/13/2021

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting

Multivariate time-series forecasting plays a crucial role in many real-w...

0 Defu Cao, et al. ∙

research

∙ 03/07/2021

Syntax-BERT: Improving Pre-trained Transformers with Syntax Trees

Pre-trained language models like BERT achieve superior performances in v...

0 Jiangang Bai, et al. ∙

research

∙ 10/14/2020

AutoADR: Automatic Model Design for Ad Relevance

Large-scale pre-trained models have attracted extensive attention in the...

4 Yiren Chen, et al. ∙

research

∙ 09/04/2020

Multivariate Time-series Anomaly Detection via Graph Attention Network

Anomaly detection on multivariate time-series is of great importance in ...

43 Hang Zhao, et al. ∙

research

∙ 08/31/2020

Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering

Knowledge-based Visual Question Answering (KVQA) requires external knowl...

0 Jing Yu, et al. ∙

research

∙ 06/16/2020

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering

Fact-based Visual Question Answering (FVQA) requires external knowledge ...

0 Zihao Zhu, et al. ∙

research

∙ 06/16/2020

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based VisualQuestion Answering

Fact-based Visual Question Answering (FVQA) requires external knowledge ...

0 Zihao Zhu, et al. ∙

research

∙ 04/08/2020

LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression

BERT is a cutting-edge language representation model pre-trained by a la...

0 Yihuan Mao, et al. ∙

research

∙ 04/08/2020

Improving BERT with Self-Supervised Attention

One of the most popular paradigms of applying large, pre-trained NLP mod...

0 Xiaoyu Kou, et al. ∙

research

∙ 01/06/2020

Deeper Insights into Weight Sharing in Neural Architecture Search

With the success of deep neural networks, Neural Architecture Search (NA...

19 Yuge Zhang, et al. ∙

research

∙ 12/23/2019

TextNAS: A Neural Architecture Search Space tailored for Text Representation

Learning text representation is crucial for text classification and othe...

0 Yujing Wang, et al. ∙

research

∙ 11/21/2019

Customized Graph Embedding: Tailoring the Embedding Vector to a Specific Application

The graph is a natural representation of data in a variety of real-world...

0 Bitan Hou, et al. ∙

research

∙ 11/18/2019

A Code injection Method for Rapid Docker Image Building

Docker images are built by layers, yet the current implementation has ma...

0 Yujing Wang, et al. ∙

research

∙ 11/06/2019

Developing a Process in Architecting Microservice Infrastructure with Docker, Kubernetes, and Istio

As an application usage grows, its owner scales up vertically by replaci...

0 Yujing Wang, et al. ∙

research

∙ 11/04/2019

Adapting a Container Infrastructure for Autonomous Vehicle Development

In the field of Autonomous Vehicle (AV) development, having a robust yet...

0 Yujing Wang, et al. ∙

research

∙ 10/10/2019

An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation

Graph Convolutional Network (GCN) has attracted intensive interests rece...

28 Nezihe Merve Gürel, et al. ∙

research

∙ 06/10/2019

Time-Series Anomaly Detection Service at Microsoft

Large companies need to monitor various metrics (for example, Page Views...

0 Hansheng Ren, et al. ∙

research

∙ 04/22/2019

A Right-of-Way Based Strategy to Implement Safe and Efficient Driving at Non-Signalized Intersections for Automated Vehicles

Non-signalized intersection is a typical and common scenario for connect...

0 Yadong Xing, et al. ∙

Yujing Wang

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