GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Hongzhan, Luo, Ziyang, Wang, Bo, Yang, Ruichao, Ma, Jing
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
by: Lin, Hongzhan, et al.
Published: (2024)

MemeArena: Automating Context-Aware Unbiased Evaluation of Harmfulness Understanding for Multimodal Large Language Models
by: Chen, Zixin, et al.
Published: (2025)

AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness
by: Chen, Zixin, et al.
Published: (2025)

MM-CRITIC: A Holistic Evaluation of Large Multimodal Models as Multimodal Critique
by: Zeng, Gailun, et al.
Published: (2025)

ScratchEval: Are GPT-4o Smarter than My Child? Evaluating Large Multimodal Models with Visual Programming Challenges
by: Fu, Rao, et al.
Published: (2024)

A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM
by: Wang, Bo, et al.
Published: (2026)

From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms
by: Luo, Jinghao, et al.
Published: (2026)

AMR-Evol: Adaptive Modular Response Evolution Elicits Better Knowledge Distillation for Large Language Models in Code Generation
by: Luo, Ziyang, et al.
Published: (2024)

MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
by: Wang, Shengkang, et al.
Published: (2024)

Reinforcement Tuning for Detecting Stances and Debunking Rumors Jointly with Large Language Models
by: Yang, Ruichao, et al.
Published: (2024)

ClarityEthic: Explainable Moral Judgment Utilizing Contrastive Ethical Insights from Large Language Models
by: Sun, Yuxi, et al.
Published: (2024)

LLM-Enhanced Multiple Instance Learning for Joint Rumor and Stance Detection with Social Context Information
by: Yang, Ruichao, et al.
Published: (2025)

Towards Low-Resource Harmful Meme Detection with LMM Agents
by: Huang, Jianzhao, et al.
Published: (2024)

Explainable Ethical Assessment on Human Behaviors by Generating Conflicting Social Norms
by: Sun, Yuxi, et al.
Published: (2025)

Knowledge-Augmented Multimodal Clinical Rationale Generation for Disease Diagnosis with Small Language Models
by: Niu, Shuai, et al.
Published: (2024)

CHiSafetyBench: A Chinese Hierarchical Safety Benchmark for Large Language Models
by: Zhang, Wenjing, et al.
Published: (2024)

VideoAutoArena: An Automated Arena for Evaluating Large Multimodal Models in Video Analysis through User Simulation
by: Luo, Ziyang, et al.
Published: (2024)

Towards Comprehensive Detection of Chinese Harmful Memes
by: Lu, Junyu, et al.
Published: (2024)

MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues
by: Liu, Zheyuan, et al.
Published: (2026)

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

MCP-SafetyBench: A Benchmark for Safety Evaluation of Large Language Models with Real-World MCP Servers
by: Zong, Xuanjun, et al.
Published: (2025)

CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models
by: Lin, Hongzhan, et al.
Published: (2024)

EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
by: Hu, He, et al.
Published: (2025)

Explainable Fake News Detection With Large Language Model via Defense Among Competing Wisdom
by: Wang, Bo, et al.
Published: (2024)

SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models
by: Li, Lijun, et al.
Published: (2024)

Probabilistic Concept Graph Reasoning for Multimodal Misinformation Detection
by: Yang, Ruichao, et al.
Published: (2026)

Graphically Speaking: Unmasking Abuse in Social Media with Conversation Insights
by: Nouri, Célia, et al.
Published: (2025)

SafeDialBench: A Fine-Grained Safety Evaluation Benchmark for Large Language Models in Multi-Turn Dialogues with Diverse Jailbreak Attacks
by: Cao, Hongye, et al.
Published: (2025)

MDIT-Bench: Evaluating the Dual-Implicit Toxicity in Large Multimodal Models
by: Jin, Bohan, et al.
Published: (2025)

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

SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models
by: Lv, Weijiang, et al.
Published: (2026)

Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench
by: Liu, Zheyuan, et al.
Published: (2024)

GOAT-SLM: A Spoken Language Model with Paralinguistic and Speaker Characteristic Awareness
by: Chen, Hongjie, et al.
Published: (2025)

ChiEngMixBench: Evaluating Large Language Models on Spontaneous and Natural Chinese-English Code-Mixed Generation
by: Yang, Qingyan, et al.
Published: (2026)

WizardCoder: Empowering Code Large Language Models with Evol-Instruct
by: Luo, Ziyang, et al.
Published: (2023)

BacktestBench: Benchmarking Large Language Models for Automated Quantitative Strategy Backtesting
by: Wang, Zhensheng, et al.
Published: (2026)

MemeCMD: An Automatically Generated Chinese Multi-turn Dialogue Dataset with Contextually Retrieved Memes
by: Wang, Yuheng, et al.
Published: (2025)

Towards Context-Invariant Safety Alignment for Large Language Models
by: Wang, Yixu, et al.
Published: (2026)

GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
by: Khanna, Mukul, et al.
Published: (2024)

RefuteBench: Evaluating Refuting Instruction-Following for Large Language Models
by: Yan, Jianhao, et al.
Published: (2024)