116 citations · 496 across the 48 of their papers we have counts for
12 papers · 1 filter
DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization
Zheqi Lv, Wenqiao Zhang, Shengyu Zhang +8
Device Model Generalization (DMG) is a practical yet under-investigated research topic for on-device machine learning applications. It aims to improve the generalization ability of…
Personalizing Intervened Network for Long-tailed Sequential User Behavior Modeling
Zheqi Lv, Feng Wang, Shengyu Zhang +3
In an era of information explosion, recommendation systems play an important role in people's daily life by facilitating content exploration. It is known that user activeness, i.e.…
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…
HERO: HiErarchical spatio-tempoRal reasOning with Contrastive Action Correspondence for End-to-End Video Object Grounding
Mengze Li, Tianbao Wang, Haoyu Zhang +6
Video Object Grounding (VOG) is the problem of associating spatial object regions in the video to a descriptive natural language query. This is a challenging vision-language task t…
Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in Videos
Juncheng Li, Junlin Xie, Linchao Zhu +8
Understanding human emotions is a crucial ability for intelligent robots to provide better human-robot interactions. The existing works are limited to trimmed video-level emotion c…
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…
BOSS: Bottom-up Cross-modal Semantic Composition with Hybrid Counterfactual Training for Robust Content-based Image Retrieval
Wenqiao Zhang, Jiannan Guo, Mengze Li +5
Content-Based Image Retrieval (CIR) aims to search for a target image by concurrently comprehending the composition of an example image and a complementary text, which potentially…
Intelligent Request Strategy Design in Recommender System
Xufeng Qian, Yue Xu, Fuyu Lv +6
Waterfall Recommender System (RS), a popular form of RS in mobile applications, is a stream of recommended items consisting of successive pages that can be browsed by scrolling. In…
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…
BoostMIS: Boosting Medical Image Semi-supervised Learning with Adaptive Pseudo Labeling and Informative Active Annotation
Wenqiao Zhang, Lei Zhu, James Hallinan +4
In this paper, we propose a novel semi-supervised learning (SSL) framework named BoostMIS that combines adaptive pseudo labeling and informative active annotation to unleash the po…
End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding
Mengze Li, Tianbao Wang, Haoyu Zhang +9
Natural language spatial video grounding aims to detect the relevant objects in video frames with descriptive sentences as the query. In spite of the great advances, most existing…
A Novel Architecture Slimming Method for Network Pruning and Knowledge Distillation
Dongqi Wang, Shengyu Zhang, Zhipeng Di +3
Network pruning and knowledge distillation are two widely-known model compression methods that efficiently reduce computation cost and model size. A common problem in both pruning…