69 citations · 87 across the 8 of their papers we have counts for
8 papers
Erasing Self-Supervised Learning Backdoor by Cluster Activation Masking
Shengsheng Qian, Dizhan Xue, Yifei Wang +3
Self-Supervised Learning (SSL) is an effective paradigm for learning representations from unlabeled data, such as text, images, and videos. However, researchers have recently found…
A Survey on Interpretable Cross-modal Reasoning
Dizhan Xue, Shengsheng Qian, Zuyi Zhou +1
In recent years, cross-modal reasoning (CMR), the process of understanding and reasoning across different modalities, has emerged as a pivotal area with applications spanning from…
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering
Jun Hu, Bryan Hooi, Shengsheng Qian +2
Graph Neural Networks (GNNs) have recently been utilized to build Collaborative Filtering (CF) models to predict user preferences based on historical user-item interactions. Howeve…
Contrastive Adaptive Propagation Graph Neural Networks for Efficient Graph Learning
Jun Hu, Shengsheng Qian, Quan Fang +1
Graph Neural Networks (GNNs) have achieved great success in processing graph data by extracting and propagating structure-aware features. Existing GNN research designs various prop…
GRecX: An Efficient and Unified Benchmark for GNN-based Recommendation
Desheng Cai, Jun Hu, Quan Zhao +3
In this paper, we present GRecX, an open-source TensorFlow framework for benchmarking GNN-based recommendation models in an efficient and unified way. GRecX consists of core librar…
HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval
Song Liu, Haoqi Fan, Shengsheng Qian +3
Video-Text Retrieval has been a hot research topic with the growth of multimedia data on the internet. Transformer for video-text learning has attracted increasing attention due to…
Efficient Graph Deep Learning in TensorFlow with tf_geometric
Jun Hu, Shengsheng Qian, Quan Fang +4
We introduce tf_geometric, an efficient and friendly library for graph deep learning, which is compatible with both TensorFlow 1.x and 2.x. tf_geometric provides kernel libraries f…
AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding
Lei Sang, Min Xu, Shengsheng Qian +1
Network embedding represents nodes in a continuous vector space and preserves structure information from the Network. Existing methods usually adopt a "one-size-fits-all" approach…