9 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Enhancing Protein Representation Learning via Manifold Restore Mixing
Yizhou Dang, Chuang Zhao, Lianbo Ma +3
Data augmentation (DA) has been proven to be an effective means for improving protein representation learning (PRL) by generating additional training samples. Although mainstream p…
cs.IR2026
Pay Attention to Sequence Split: Uncovering the Impacts of Sub-Sequence Splitting on Sequential Recommendation Models
Yizhou Dang, Yifan Wu, Minhan Huang +5
Sub-sequence splitting (SSS) has been demonstrated as an effective approach to mitigate data sparsity in sequential recommendation (SR) by splitting a raw user interaction sequence…
cs.IR2023★ 9 cited
Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects
Xinghua Qu, Hongyang Liu, Zhu Sun +4
Conversational recommender systems (CRSs) have become crucial emerging research topics in the field of RSs, thanks to their natural advantages of explicitly acquiring user preferen…