activity
20212024
most citedCauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation

116 citations · 133 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2024

A General and Flexible Multi-concept Parsing Framework for Multilingual Semantic Matching

Dong Yao

Sentence semantic matching is a research hotspot in natural language processing, which is considerably significant in various key scenarios, such as community question answering, s…

cs.SD2023

MART: Learning Hierarchical Music Audio Representations with Part-Whole Transformer

Dong Yao, Jieming Zhu, Jiahao Xun +6

Recent research in self-supervised contrastive learning of music representations has demonstrated remarkable results across diverse downstream tasks. However, a prevailing trend in…

cs.IR2023

Denoising Multi-modal Sequential Recommenders with Contrastive Learning

Dong Yao, Shengyu Zhang, Zhou Zhao +5

There is a rapidly-growing research interest in engaging users with multi-modal data for accurate user modeling on recommender systems. Existing multimedia recommenders have achiev…

cs.IR2022

CCL4Rec: Contrast over Contrastive Learning for Micro-video Recommendation

Shengyu Zhang, Bofang Li, Dong Yao +7

Micro-video recommender systems suffer from the ubiquitous noises in users' behaviors, which might render the learned user representation indiscriminating, and lead to trivial reco…

cs.IR2022

Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation

Shengyu Zhang, Lingxiao Yang, Dong Yao +5

Effectively representing users lie at the core of modern recommender systems. Since users' interests naturally exhibit multiple aspects, it is of increasing interest to develop mul…

cs.SD2022★ 17 cited

Contrastive Learning with Positive-Negative Frame Mask for Music Representation

Dong Yao, Zhou Zhao, Shengyu Zhang +4

Self-supervised learning, especially contrastive learning, has made an outstanding contribution to the development of many deep learning research fields. Recently, researchers in t…

cs.IR2021★ 116 cited

CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation

Shengyu Zhang, Dong Yao, Zhou Zhao +2

Learning user representations based on historical behaviors lies at the core of modern recommender systems. Recent advances in sequential recommenders have convincingly demonstrate…

cs.CV2021

Modeling High-order Interactions across Multi-interests for Micro-video Recommendation

Dong Yao, Shengyu Zhang, Zhou Zhao +4

Personalized recommendation system has become pervasive in various video platform. Many effective methods have been proposed, but most of them didn't capture the user's multi-level…