18 citations · 64 across the 14 of their papers we have counts for
15 papers
PREMISE: Matching-based Prediction for Accurate Review Recommendation
Wei Han, Hui Chen, Soujanya Poria
We present PREMISE (PREdict with Matching ScorEs), a new architecture for the matching-based learning in the multimodal fields for the multimodal review helpfulness (MRHP) task. Di…
Towards Robust Instruction Tuning on Multimodal Large Language Models
Wei Han, Hui Chen, Soujanya Poria
Fine-tuning large language models (LLMs) on multi-task instruction-following data has been proven to be a powerful learning paradigm for improving their zero-shot capabilities on n…
Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models
Wei Han, Hui Chen, Min-Yen Kan +1
Video question-answering is a fundamental task in the field of video understanding. Although current vision--language models (VLMs) equipped with Video Transformers have enabled te…
Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet Extraction
Yew Ken Chia, Hui Chen, Wei Han +4
Aspect Sentiment Triplet Extraction (ASTE) is a challenging task in sentiment analysis, aiming to provide fine-grained insights into human sentiments. However, existing benchmarks…
MM-Align: Learning Optimal Transport-based Alignment Dynamics for Fast and Accurate Inference on Missing Modality Sequences
Wei Han, Hui Chen, Min-Yen Kan +1
Existing multimodal tasks mostly target at the complete input modality setting, i.e., each modality is either complete or completely missing in both training and test sets. However…
SAT: Improving Semi-Supervised Text Classification with Simple Instance-Adaptive Self-Training
Hui Chen, Wei Han, Soujanya Poria
Self-training methods have been explored in recent years and have exhibited great performance in improving semi-supervised learning. This work presents a Simple instance-Adaptive s…
SANCL: Multimodal Review Helpfulness Prediction with Selective Attention and Natural Contrastive Learning
Wei Han, Hui Chen, Zhen Hai +2
With the boom of e-commerce, Multimodal Review Helpfulness Prediction (MRHP), which aims to sort product reviews according to the predicted helpfulness scores has become a research…
DoubleMix: Simple Interpolation-Based Data Augmentation for Text Classification
Hui Chen, Wei Han, Diyi Yang +1
This paper proposes a simple yet effective interpolation-based data augmentation approach termed DoubleMix, to improve the robustness of models in text classification. DoubleMix fi…
Multi-trends Enhanced Dynamic Micro-video Recommendation
Yujie Lu, Yingxuan Huang, Shengyu Zhang +4
The explosively generated micro-videos on content sharing platforms call for recommender systems to permit personalized micro-video discovery with ease. Recent advances in micro-vi…
Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis
Wei Han, Hui Chen, Soujanya Poria
In multimodal sentiment analysis (MSA), the performance of a model highly depends on the quality of synthesized embeddings. These embeddings are generated from the upstream process…
Bi-Bimodal Modality Fusion for Correlation-Controlled Multimodal Sentiment Analysis
Wei Han, Hui Chen, Alexander Gelbukh +3
Multimodal sentiment analysis aims to extract and integrate semantic information collected from multiple modalities to recognize the expressed emotions and sentiment in multimodal…
Persuasive Dialogue Understanding: the Baselines and Negative Results
Hui Chen, Deepanway Ghosal, Navonil Majumder +2
Persuasion aims at forming one's opinion and action via a series of persuasive messages containing persuader's strategies. Due to its potential application in persuasive dialogue s…
Decision-Aware Conditional GANs for Time Series Data
He Sun, Zhun Deng, Hui Chen +1
We introduce the decision-aware time-series conditional generative adversarial network (DAT-CGAN) as a method for time-series generation. The framework adopts a multi-Wasserstein l…
Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention Networks
Hui Chen, Pengfei Hong, Wei Han +2
Dialogue relation extraction (DRE) aims to detect the relation between two entities mentioned in a multi-party dialogue. It plays an important role in constructing knowledge graphs…
UER: An Open-Source Toolkit for Pre-training Models
Zhe Zhao, Hui Chen, Jinbin Zhang +7
Existing works, including ELMO and BERT, have revealed the importance of pre-training for NLP tasks. While there does not exist a single pre-training model that works best in all c…