Zeyu Cui | DeepAI

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∙ 12/08/2022

OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models

Generalist models, which are capable of performing diverse multi-modal t...

0 Jinze Bai, et al. ∙

∙ 11/29/2022

MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition

In this paper, we propose a novel multi-modal multi-task encoder-decoder...

0 Xiaohuan Zhou, et al. ∙

∙ 11/26/2022

Contextual Expressive Text-to-Speech

The goal of expressive Text-to-speech (TTS) is to synthesize natural spe...

0 Jianhong Tu, et al. ∙

∙ 05/17/2022

M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems

Industrial recommender systems have been growing increasingly complex, m...

0 Zeyu Cui, et al. ∙

∙ 05/25/2021

GraphFM: Graph Factorization Machines for Feature Interaction Modeling

Factorization machine (FM) is a prevalent approach to modeling pairwise ...

7 Zekun Li, et al. ∙

∙ 04/26/2021

Represent Items by Items: An Enhanced Representation of the Target Item for Recommendation

Item-based collaborative filtering (ICF) has been widely used in industr...

0 Yinjiang Cai, et al. ∙

∙ 04/07/2021

DyGCN: Dynamic Graph Embedding with Graph Convolutional Network

Graph embedding, aiming to learn low-dimensional representations (aka. e...

43 Zeyu Cui, et al. ∙

∙ 02/22/2021

Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval

The ad-hoc retrieval task is to rank related documents given a query and...

0 Xueli Yu, et al. ∙

∙ 01/28/2021

A Graph-based Relevance Matching Model for Ad-hoc Retrieval

To retrieve more relevant, appropriate and useful documents given a quer...

0 Yufeng Zhang, et al. ∙

∙ 08/17/2020

Disentangled Item Representation for Recommender Systems

Item representations in recommendation systems are expected to reveal th...

0 Zeyu Cui, et al. ∙

∙ 04/22/2020

Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks

Text classification is fundamental in natural language processing (NLP),...

0 Yufeng Zhang, et al. ∙

∙ 10/12/2019

Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction

Click-through rate (CTR) prediction is an essential task in web applicat...

0 Zekun Li, et al. ∙

∙ 07/31/2019

Semi-supervised Compatibility Learning Across Categories for Clothing Matching

Learning the compatibility between fashion items across categories is a ...

0 Zekun Li, et al. ∙

∙ 02/21/2019

Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks

With the rapid development of fashion market, the customers' demands of ...

0 Zeyu Cui, et al. ∙

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