Cover Image

Self-HarmLLM: Can Large Language Model Harm Itself?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Heehwan, Park, Sungjune, Choi, Daeseon
Format:	Preprint
Published:	2025
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

Judgment-of-Thought Prompting: A Courtroom-Inspired Framework for Binary Logical Reasoning with Large Language Models
by: Park, Sungjune, et al.
Published: (2024)

Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation
by: Huang, Tiansheng, et al.
Published: (2024)

HarmMetric Eval: Benchmarking Metrics and Judges for LLM Harmfulness Assessment
by: Yang, Langqi, et al.
Published: (2025)

AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
by: Andriushchenko, Maksym, et al.
Published: (2024)

SocialHarmBench: Revealing LLM Vulnerabilities to Socially Harmful Requests
by: Pandey, Punya Syon, et al.
Published: (2025)

`For Argument's Sake, Show Me How to Harm Myself!': Jailbreaking LLMs in Suicide and Self-Harm Contexts
by: Schoene, Annika M, et al.
Published: (2025)

Large Language Models are Vulnerable to Bait-and-Switch Attacks for Generating Harmful Content
by: Bianchi, Federico, et al.
Published: (2024)

FairBelief -- Assessing Harmful Beliefs in Language Models
by: Setzu, Mattia, et al.
Published: (2024)

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

Moderating Harm: Benchmarking Large Language Models for Cyberbullying Detection in YouTube Comments
by: Muminovic, Amel
Published: (2025)

VaccineRAG: Boosting Multimodal Large Language Models' Immunity to Harmful RAG Samples
by: Sun, Qixin, et al.
Published: (2025)

Harm or Humor: A Multimodal, Multilingual Benchmark for Overt and Covert Harmful Humor
by: Sharshar, Ahmed, et al.
Published: (2026)

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

PluriHarms: Benchmarking the Full Spectrum of Human Judgments on AI Harm
by: Li, Jing-Jing, et al.
Published: (2026)

HALF: Harm-Aware LLM Fairness Evaluation Aligned with Deployment
by: Mekky, Ali, et al.
Published: (2025)

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

HarmTransform: Transforming Explicit Harmful Queries into Stealthy via Multi-Agent Debate
by: Zhu, Shenzhe
Published: (2025)

Helpful or Harmful? Exploring the Efficacy of Large Language Models for Online Grooming Prevention
by: Prosser, Ellie, 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)

Advancing Harmful Content Detection in Organizational Research: Integrating Large Language Models with Elo Rating System
by: Akben, Mustafa, et al.
Published: (2025)

Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation
by: Wang, Yibo, et al.
Published: (2025)

REVEAL: Multi-turn Evaluation of Image-Input Harms for Vision LLM
by: Jindal, Madhur, et al.
Published: (2025)

Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity
by: Qu, Jiaming, et al.
Published: (2026)

Harmful Suicide Content Detection
by: Park, Kyumin, et al.
Published: (2024)

Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024)

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

Survival at Any Cost? LLMs and the Choice Between Self-Preservation and Human Harm
by: Mohamadi, Alireza, et al.
Published: (2025)

Look Before You Leap: Enhancing Attention and Vigilance Regarding Harmful Content with GuidelineLLM
by: Zhang, Shaoqing, et al.
Published: (2024)

Virus: Harmful Fine-tuning Attack for Large Language Models Bypassing Guardrail Moderation
by: Huang, Tiansheng, et al.
Published: (2025)

Human-Guided Harm Recovery for Computer Use Agents
by: Li, Christy, et al.
Published: (2026)

Beyond Static Benchmarks: Synthesizing Harmful Content via Persona-based Simulation for Robust Evaluation
by: Lee, Huije, et al.
Published: (2026)

Memorizing Documents with Guidance in Large Language Models
by: Park, Bumjin, et al.
Published: (2024)

Unintended Harms of Value-Aligned LLMs: Psychological and Empirical Insights
by: Choi, Sooyung, et al.
Published: (2025)

RealHarm: A Collection of Real-World Language Model Application Failures
by: Jeune, Pierre Le, et al.
Published: (2025)

Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models
by: Kim, Yeeun, et al.
Published: (2024)

Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning
by: Xia, Haizhou
Published: (2026)

More of the Same: Persistent Representational Harms Under Increased Representation
by: Mickel, Jennifer, et al.
Published: (2025)

Beyond Accuracy: An Explainability-Driven Analysis of Harmful Content Detection
by: Dhara, Trishita, et al.
Published: (2026)

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism
by: Orgad, Hadas, et al.
Published: (2026)

Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms
by: Oak, Rajvardhan, et al.
Published: (2025)