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Fuqing Zhu

8 accepted papers

2024

Uncertainty-Aware Cross-Modal Alignment for Hate Speech Detection

COLING 2024main

Hate speech detection has become an urgent task with the emergence of huge multimodal harmful content (, memes) on social media platforms. Previous studies mainly focus on complex feature extraction and fusion to learn discriminative information from memes. However, these methods ignore two key poin…

Cited by 1SourcePDFScholar
2024

Uncertainty-Guided Modal Rebalance for Hateful Memes Detection

ACL 2024long

Hateful memes detection is a challenging multimodal understanding task that requires comprehensive learning of vision, language, and cross-modal interactions. Previous research has focused on developing effective fusion strategies for integrating hate information from different modalities. However,…

Cited by 0SourcePDFScholar
2023

QAP: A Quantum-Inspired Adaptive-Priority-Learning Model for Multimodal Emotion Recognition

ACL 2023findings

Multimodal emotion recognition for video has gained considerable attention in recent years, in which three modalities (i.e., textual, visual and acoustic) are involved. Due to the diverse levels of informational content related to emotion, three modalities typically possess varying degrees of contri…

Cited by 16SourcePDFScholar
2022

Cross-Layer Aggregation with Transformers for Multi-Label Image Classification

ICASSP 2022accepted

Multi-label image classification task aims to predict multiple object labels in a given image and faces the challenge of variable-sized objects. Limited by the size of CNN convolution kernels, existing CNN-based methods have difficulty capturing global dependencies and effectively fusing multiple la…

Cited by 0SourceScholar
2021

Aligning the training and evaluation of unsupervised text style Transfer

ICASSP 2021accepted

In the text style transfer task, models modify the attribute style of given texts while keeping the style-irrelevant content unchanged. Previous work has proposed many approaches on the non-parallel corpus (without style-to-style training pairs). These approaches are mostly motivated by heuristic in…

Cited by 0SourceScholar
2021

An Adaptive Hybrid Framework for Cross-domain Aspect-based Sentiment Analysis

AAAI 2021technical

Cross-domain aspect-based sentiment analysis aims to utilize the useful knowledge in a source domain to extract aspect terms and predict their sentiment polarities in a target domain. Recently, methods based on adversarial training have been applied to this task and achieved promising results. In su…

Cited by 35SourcePDFScholar