167 citations · 252 across the 8 of their papers we have counts for
10 papers
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…
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…
Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis
Sijie Mai, Ying Zeng, Shuangjia Zheng +1
The wide application of smart devices enables the availability of multimodal data, which can be utilized in many tasks. In the field of multimodal sentiment analysis (MSA), most pr…
Graph Capsule Aggregation for Unaligned Multimodal Sequences
Jianfeng Wu, Sijie Mai, Haifeng Hu
Humans express their opinions and emotions through multiple modalities which mainly consist of textual, acoustic and visual modalities. Prior works on multimodal sentiment analysis…