54 citations · 286 across the 25 of their papers we have counts for
27 papers
KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction
Han Liu, Keyan Ding, Peilin Chen +4
Accurate prediction of protein-ligand binding affinity is critical for drug discovery. While recent deep learning approaches have demonstrated promising results, they often rely so…
Mitigating Hallucination Through Theory-Consistent Symmetric Multimodal Preference Optimization
Wenqi Liu, Xuemeng Song, Jiaxi Li +4
Direct Preference Optimization (DPO) has emerged as an effective approach for mitigating hallucination in Multimodal Large Language Models (MLLMs). Although existing methods have a…
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
Han Liu, Yinwei Wei, Fan Liu +3
Multimodal information (e.g., visual, acoustic, and textual) has been widely used to enhance representation learning for micro-video recommendation. For integrating multimodal info…
Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image Retrieval
Haokun Wen, Xuemeng Song, Xiaolin Chen +3
Composed image retrieval (CIR) aims to retrieve the target image based on a multimodal query, i.e., a reference image paired with corresponding modification text. Recent CIR studie…
MMGRec: Multimodal Generative Recommendation with Transformer Model
Han Liu, Yinwei Wei, Xuemeng Song +3
Multimodal recommendation aims to recommend user-preferred candidates based on her/his historically interacted items and associated multimodal information. Previous studies commonl…
Attribute-driven Disentangled Representation Learning for Multimodal Recommendation
Zhenyang Li, Fan Liu, Yinwei Wei +3
Recommendation algorithms forecast user preferences by correlating user and item representations derived from historical interaction patterns. In pursuit of enhanced performance, m…
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation
Yunshan Ma, Yingzhi He, Xiang Wang +4
Bundle recommendation seeks to recommend a bundle of related items to users to improve both user experience and the profits of platform. Existing bundle recommendation models have…
Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction
Yunshan Ma, Xiaohao Liu, Yinwei Wei +3
Automatic bundle construction is a crucial prerequisite step in various bundle-aware online services. Previous approaches are mostly designed to model the bundling strategy of exis…
Target-Guided Composed Image Retrieval
Haokun Wen, Xian Zhang, Xuemeng Song +2
Composed image retrieval (CIR) is a new and flexible image retrieval paradigm, which can retrieve the target image for a multimodal query, including a reference image and its corre…
Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation
Wei Ji, Xiangyan Liu, An Zhang +3
Multi-modal recommendation systems, which integrate diverse types of information, have gained widespread attention in recent years. However, compared to traditional collaborative f…
General Debiasing for Multimodal Sentiment Analysis
Teng Sun, Juntong Ni, Wenjie Wang +3
Existing work on Multimodal Sentiment Analysis (MSA) utilizes multimodal information for prediction yet unavoidably suffers from fitting the spurious correlations between multimoda…
StyleEDL: Style-Guided High-order Attention Network for Image Emotion Distribution Learning
Peiguang Jing, Xianyi Liu, Ji Wang +3
Emotion distribution learning has gained increasing attention with the tendency to express emotions through images. As for emotion ambiguity arising from humans' subjectivity, subs…
Revisiting Conversation Discourse for Dialogue Disentanglement
Bobo Li, Hao Fei, Fei Li +5
Dialogue disentanglement aims to detach the chronologically ordered utterances into several independent sessions. Conversation utterances are essentially organized and described by…
Dual Semantic Knowledge Composed Multimodal Dialog Systems
Xiaolin Chen, Xuemeng Song, Yinwei Wei +2
Textual response generation is an essential task for multimodal task-oriented dialog systems.Although existing studies have achieved fruitful progress, they still suffer from two c…
Micro-video Tagging via Jointly Modeling Social Influence and Tag Relation
Xiao Wang, Tian Gan, Yinwei Wei +3
The last decade has witnessed the proliferation of micro-videos on various user-generated content platforms. According to our statistics, around 85.7\% of micro-videos lack annotat…
HS-GCN: Hamming Spatial Graph Convolutional Networks for Recommendation
Han Liu, Yinwei Wei, Jianhua Yin +1
An efficient solution to the large-scale recommender system is to represent users and items as binary hash codes in the Hamming space. Towards this end, existing methods tend to co…
MRTNet: Multi-Resolution Temporal Network for Video Sentence Grounding
Wei Ji, Long Chen, Yinwei Wei +2
Given an untrimmed video and natural language query, video sentence grounding aims to localize the target temporal moment in the video. Existing methods mainly tackle this task by…
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…
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…
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…
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…
Dual Preference Distribution Learning for Item Recommendation
Xue Dong, Xuemeng Song, Na Zheng +2
Recommender systems can automatically recommend users with items that they probably like. The goal of them is to model the user-item interaction by effectively representing the use…
GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Wei Yinwei, Wang Xiang, Nie Liqiang +2
Reorganizing implicit feedback of users as a user-item interaction graph facilitates the applications of graph convolutional networks (GCNs) in recommendation tasks. In the interac…