167 citations · 272 across the 17 of their papers we have counts for
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Addressing Missing and Noisy Modalities in One Solution: Unified Modality-Quality Framework for Low-quality Multimodal Data
Sijie Mai, Shiqin Han, Haifeng Hu
Multimodal data encountered in real-world scenarios are typically of low quality, with noisy modalities and missing modalities being typical forms that severely hinder model perfor…
CyIN: Cyclic Informative Latent Space for Bridging Complete and Incomplete Multimodal Learning
Ronghao Lin, Qiaolin He, Sijie Mai +5
Multimodal machine learning, mimicking the human brain's ability to integrate various modalities has seen rapid growth. Most previous multimodal models are trained on perfectly pai…
Meta-Learn Unimodal Signals with Weak Supervision for Multimodal Sentiment Analysis
Sijie Mai, Yu Zhao, Ying Zeng +2
Multimodal sentiment analysis aims to effectively integrate information from various sources to infer sentiment, where in many cases there are no annotations for unimodal labels. T…
Curriculum Learning Meets Weakly Supervised Modality Correlation Learning
Sijie Mai, Ya Sun, Haifeng Hu
In the field of multimodal sentiment analysis (MSA), a few studies have leveraged the inherent modality correlation information stored in samples for self-supervised learning. Howe…
Relation-dependent Contrastive Learning with Cluster Sampling for Inductive Relation Prediction
Jianfeng Wu, Sijie Mai, Haifeng Hu
Relation prediction is a task designed for knowledge graph completion which aims to predict missing relationships between entities. Recent subgraph-based models for inductive relat…
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal Representations
Sijie Mai, Ying Zeng, Haifeng Hu
Learning effective joint embedding for cross-modal data has always been a focus in the field of multimodal machine learning. We argue that during multimodal fusion, the generated m…
Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
Jiahua Rao, Shuangjia Zheng, Sijie Mai +1
Illuminating the interconnections between drugs and genes is an important topic in drug development and precision medicine. Currently, computational predictions of drug-gene intera…
Which is Making the Contribution: Modulating Unimodal and Cross-modal Dynamics for Multimodal Sentiment Analysis
Ying Zeng, Sijie Mai, Haifeng Hu
Multimodal sentiment analysis (MSA) draws increasing attention with the availability of multimodal data. The boost in performance of MSA models is mainly hindered by two problems.…
Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning
Shuangjia Zheng, Sijie Mai, Ya Sun +2
Link prediction for knowledge graphs aims to predict missing connections between entities. Prevailing methods are limited to a transductive setting and hard to process unseen entit…