activity
20192022
most citedFi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction

234 citations · 450 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2022★ 3 cited

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

Jinze Bai, Rui Men, Hao Yang +15

Generalist models, which are capable of performing diverse multi-modal tasks in a task-agnostic way within a single model, have been explored recently. Being, hopefully, an alterna…

cs.MM2022★ 1 cited

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

Xiaohuan Zhou, Jiaming Wang, Zeyu Cui +4

In this paper, we propose a novel multi-modal multi-task encoder-decoder pre-training framework (MMSpeech) for Mandarin automatic speech recognition (ASR), which employs both unlab…

eess.AS2022

Contextual Expressive Text-to-Speech

Jianhong Tu, Zeyu Cui, Xiaohuan Zhou +4

The goal of expressive Text-to-speech (TTS) is to synthesize natural speech with desired content, prosody, emotion, or timbre, in high expressiveness. Most of previous studies atte…

cs.IR2022★ 27 cited

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

Zeyu Cui, Jianxin Ma, Chang Zhou +2

Industrial recommender systems have been growing increasingly complex, may involve \emph{diverse domains} such as e-commerce products and user-generated contents, and can comprise…

cs.LG2021★ 7 cited

GraphFM: Graph Factorization Machines for Feature Interaction Modeling

Shu Wu, Zekun Li, Yunyue Su +3

Factorization machine (FM) is a prevalent approach to modeling pairwise (second-order) feature interactions when dealing with high-dimensional sparse data. However, on the one hand…

cs.IR2021★ 2 cited

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

Yinjiang Cai, Zeyu Cui, Shu Wu +2

Item-based collaborative filtering (ICF) has been widely used in industrial applications such as recommender system and online advertising. It models users' preference on target it…