297 citations · 2.2k across the 85 of their papers we have counts for
22 papers · 1 filter
Multi-queue Momentum Contrast for Microvideo-Product Retrieval
Yali Du, Yinwei Wei, Wei Ji +3
The booming development and huge market of micro-videos bring new e-commerce channels for merchants. Currently, more micro-video publishers prefer to embed relevant ads into their…
Causal Inference for Knowledge Graph based Recommendation
Yinwei Wei, Xiang Wang, Liqiang Nie +3
Knowledge Graph (KG), as a side-information, tends to be utilized to supplement the collaborative filtering (CF) based recommendation model. By mapping items with the entities in K…
Multimodal Matching-aware Co-attention Networks with Mutual Knowledge Distillation for Fake News Detection
Linmei Hu, Ziwang Zhao, Weijian Qi +2
Fake news often involves multimedia information such as text and image to mislead readers, proliferating and expanding its influence. Most existing fake news detection methods appl…
A Survey of Knowledge Enhanced Pre-trained Language Models
Linmei Hu, Zeyi Liu, Ziwang Zhao +3
Pre-trained Language Models (PLMs) which are trained on large text corpus via self-supervised learning method, have yielded promising performance on various tasks in Natural Langua…
Privacy-Preserving Synthetic Data Generation for Recommendation Systems
Fan Liu, Zhiyong Cheng, Huilin Chen +3
Recommendation systems make predictions chiefly based on users' historical interaction data (e.g., items previously clicked or purchased). There is a risk of privacy leakage when c…
Deep Convolutional Pooling Transformer for Deepfake Detection
Tianyi Wang, Harry Cheng, Kam Pui Chow +1
Recently, Deepfake has drawn considerable public attention due to security and privacy concerns in social media digital forensics. As the wildly spreading Deepfake videos on the In…
Visual Perturbation-aware Collaborative Learning for Overcoming the Language Prior Problem
Yudong Han, Liqiang Nie, Jianhua Yin +2
Several studies have recently pointed that existing Visual Question Answering (VQA) models heavily suffer from the language prior problem, which refers to capturing superficial sta…
Counterfactual Reasoning for Out-of-distribution Multimodal Sentiment Analysis
Teng Sun, Wenjie Wang, Liqiang Jing +3
Existing studies on multimodal sentiment analysis heavily rely on textual modality and unavoidably induce the spurious correlations between textual words and sentiment labels. This…
Semantic-aware Modular Capsule Routing for Visual Question Answering
Yudong Han, Jianhua Yin, Jianlong Wu +2
Visual Question Answering (VQA) is fundamentally compositional in nature, and many questions are simply answered by decomposing them into modular sub-problems. The recent proposed…
Lipschitz Continuity Retained Binary Neural Network
Yuzhang Shang, Dan Xu, Bin Duan +3
Relying on the premise that the performance of a binary neural network can be largely restored with eliminated quantization error between full-precision weight vectors and their co…
Network Binarization via Contrastive Learning
Yuzhang Shang, Dan Xu, Ziliang Zong +2
Neural network binarization accelerates deep models by quantizing their weights and activations into 1-bit. However, there is still a huge performance gap between Binary Neural Net…
Multimodal Dialog Systems with Dual Knowledge-enhanced Generative Pretrained Language Model
Xiaolin Chen, Xuemeng Song, Liqiang Jing +3
Text response generation for multimodal task-oriented dialog systems, which aims to generate the proper text response given the multimodal context, is an essential yet challenging…
A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA
Yangyang Guo, Liqiang Nie, Yongkang Wong +3
Knowledge-based Visual Question Answering (VQA) expects models to rely on external knowledge for robust answer prediction. Though significant it is, this paper discovers several le…
User-controllable Recommendation Against Filter Bubbles
Wenjie Wang, Fuli Feng, Liqiang Nie +1
Recommender systems usually face the issue of filter bubbles: overrecommending homogeneous items based on user features and historical interactions. Filter bubbles will grow along…
Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation
Xingning Dong, Tian Gan, Xuemeng Song +3
Scene Graph Generation, which generally follows a regular encoder-decoder pipeline, aims to first encode the visual contents within the given image and then parse them into a compa…
Image-text Retrieval: A Survey on Recent Research and Development
Min Cao, Shiping Li, Juntao Li +2
In the past few years, cross-modal image-text retrieval (ITR) has experienced increased interest in the research community due to its excellent research value and broad real-world…
Disentangled Multimodal Representation Learning for Recommendation
Fan Liu, Huilin Chen, Zhiyong Cheng +3
Many multimodal recommender systems have been proposed to exploit the rich side information associated with users or items (e.g., user reviews and item images) for learning better…
Voice-Face Homogeneity Tells Deepfake
Harry Cheng, Yangyang Guo, Tianyi Wang +3
Detecting forgery videos is highly desirable due to the abuse of deepfake. Existing detection approaches contribute to exploring the specific artifacts in deepfake videos and fit w…
MERIt: Meta-Path Guided Contrastive Learning for Logical Reasoning
Fangkai Jiao, Yangyang Guo, Xuemeng Song +1
Logical reasoning is of vital importance to natural language understanding. Previous studies either employ graph-based models to incorporate prior knowledge about logical relations…
On Modality Bias Recognition and Reduction
Yangyang Guo, Liqiang Nie, Harry Cheng +3
Making each modality in multi-modal data contribute is of vital importance to learning a versatile multi-modal model. Existing methods, however, are often dominated by one or few o…
Joint Answering and Explanation for Visual Commonsense Reasoning
Zhenyang Li, Yangyang Guo, Kejie Wang +3
Visual Commonsense Reasoning (VCR), deemed as one challenging extension of the Visual Question Answering (VQA), endeavors to pursue a more high-level visual comprehension. It is co…
Win the Lottery Ticket via Fourier Analysis: Frequencies Guided Network Pruning
Yuzhang Shang, Bin Duan, Ziliang Zong +2
With the remarkable success of deep learning recently, efficient network compression algorithms are urgently demanded for releasing the potential computational power of edge device…