Cover Image

Detecting and Mitigating Hateful Content in Multimodal Memes with Vision-Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Van, Minh-Hao, Wu, Xintao
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection
by: Mei, Jingbiao, et al.
Published: (2025)

FBHM: Functional Benchmarking and Steering of VLMs for Hateful Meme Detection
by: Bhaskar, Paramananda, et al.
Published: (2026)

Text or Image? What is More Important in Cross-Domain Generalization Capabilities of Hate Meme Detection Models?
by: Aggarwal, Piush, et al.
Published: (2024)

Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis
by: Verma, Prateek, et al.
Published: (2024)

MemeIntel: Explainable Detection of Propagandistic and Hateful Memes
by: Kmainasi, Mohamed Bayan, et al.
Published: (2025)

OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst
by: Cao, Jingtao, et al.
Published: (2024)

On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study
by: Van, Minh-Hao, et al.
Published: (2024)

MemeMind: A Large-Scale Multimodal Dataset with Chain-of-Thought Reasoning for Harmful Meme Detection
by: Gu, Hexiang, et al.
Published: (2025)

Detecting and Understanding Hateful Contents in Memes Through Captioning and Visual Question-Answering
by: Anaissi, Ali, et al.
Published: (2025)

Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
by: Zhong, Weihong, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
by: Wu, Jiulong, et al.
Published: (2025)

Beyond Translation: Cross-Cultural Meme Transcreation with Vision-Language Models
by: Zhao, Yuming, et al.
Published: (2026)

Object Detection with Multimodal Large Vision-Language Models: An In-depth Review
by: Sapkota, Ranjan, et al.
Published: (2025)

Evolver: Chain-of-Evolution Prompting to Boost Large Multimodal Models for Hateful Meme Detection
by: Huang, Jinfa, et al.
Published: (2024)

Mitigating Multilingual Hallucination in Large Vision-Language Models
by: Qu, Xiaoye, et al.
Published: (2024)

KGAlign: Joint Semantic-Structural Knowledge Encoding for Multimodal Fake News Detection
by: La, Tuan-Vinh, et al.
Published: (2025)

Robust Influence-based Training Methods for Noisy Brain MRI
by: Van, Minh-Hao, et al.
Published: (2024)

ArMeme: Propagandistic Content in Arabic Memes
by: Alam, Firoj, et al.
Published: (2024)

Exploring the Limits of Zero Shot Vision Language Models for Hate Meme Detection: The Vulnerabilities and their Interpretations
by: Rizwan, Naquee, et al.
Published: (2024)

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images
by: You, Liangliang, et al.
Published: (2025)

Explainable Multimodal Sentiment Analysis on Bengali Memes
by: Elahi, Kazi Toufique, et al.
Published: (2023)

Modularized Networks for Few-shot Hateful Meme Detection
by: Cao, Rui, et al.
Published: (2024)

Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
by: Cahyawijaya, Samuel, et al.
Published: (2026)

Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models
by: Chen, Xinlong, et al.
Published: (2025)

Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback
by: Xiao, Wenyi, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, et al.
Published: (2024)

Delve into Visual Contrastive Decoding for Hallucination Mitigation of Large Vision-Language Models
by: Lee, Yi-Lun, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
by: Manevich, Avshalom, et al.
Published: (2024)

Unveiling the "Fairness Seesaw": Discovering and Mitigating Gender and Race Bias in Vision-Language Models
by: Lan, Jian, et al.
Published: (2025)

Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
by: An, Wenbin, et al.
Published: (2024)

DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
by: Wu, Zhiyu, et al.
Published: (2024)

TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention
by: Duan, Jinhao, et al.
Published: (2025)

NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors
by: Ren, Lingfeng, et al.
Published: (2026)

Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models
by: Woo, Sangmin, et al.
Published: (2025)

MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models
by: Yan, Qiao, et al.
Published: (2025)

A Multimodal Recaptioning Framework to Account for Perceptual Diversity Across Languages in Vision-Language Modeling
by: Buettner, Kyle, et al.
Published: (2025)

Learning Compact Vision Tokens for Efficient Large Multimodal Models
by: Tang, Hao, et al.
Published: (2025)

Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features
by: Mitra, Chancharik, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
by: Wang, Xintong, et al.
Published: (2024)

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention
by: Ye, Zekai, et al.
Published: (2025)