Cover Image

Jailbreaking Multimodal Large Language Models using Multi-Clip Video

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kang, Choongwon, Sun, Seungjong, Jun, Hyunmin, Kim, Jang Hyun
Format:	Preprint
Published:	2026
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

Think While Watching: Online Streaming Segment-Level Memory for Multi-Turn Video Reasoning in Multimodal Large Language Models
by: Wang, Lu, et al.
Published: (2026)

E$^2$AT: Multimodal Jailbreak Defense via Dynamic Joint Optimization for Multimodal Large Language Models
by: Lu, Liming, et al.
Published: (2025)

Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
by: Shi, Yang, et al.
Published: (2025)

TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding
by: Ren, Shuhuai, et al.
Published: (2023)

M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation
by: Park, Jonggwon, et al.
Published: (2024)

Model Composition for Multimodal Large Language Models
by: Chen, Chi, et al.
Published: (2024)

Speaking Beyond Language: A Large-Scale Multimodal Dataset for Learning Nonverbal Cues from Video-Grounded Dialogues
by: Kim, Youngmin, et al.
Published: (2025)

MMRefine: Unveiling the Obstacles to Robust Refinement in Multimodal Large Language Models
by: Paik, Gio, et al.
Published: (2025)

Weakly Supervised Gaussian Contrastive Grounding with Large Multimodal Models for Video Question Answering
by: Wang, Haibo, et al.
Published: (2024)

Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models
by: Li, You, et al.
Published: (2025)

Can Video Large Multimodal Models Think Like Doubters-or Double-Down: A Study on Defeasible Video Entailment
by: Zhang, Yue, et al.
Published: (2025)

Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024)

VLind-Bench: Measuring Language Priors in Large Vision-Language Models
by: Lee, Kang-il, et al.
Published: (2024)

From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models
by: Jin, Haibo, et al.
Published: (2025)

Jailbreaking Safeguarded Text-to-Image Models via Large Language Models
by: Jiang, Zhengyuan, et al.
Published: (2025)

Resource-Efficient Medical Report Generation using Large Language Models
by: Abdullah, et al.
Published: (2024)

Hybrid-Level Instruction Injection for Video Token Compression in Multi-modal Large Language Models
by: Liu, Zhihang, et al.
Published: (2025)

Benchmarking Multimodal Large Language Models for Face Recognition
by: Shahreza, Hatef Otroshi, et al.
Published: (2025)

A Survey on Benchmarks of Multimodal Large Language Models
by: Li, Jian, et al.
Published: (2024)

A Survey on Evaluation of Multimodal Large Language Models
by: Huang, Jiaxing, et al.
Published: (2024)

A Survey on Agentic Multimodal Large Language Models
by: Yao, Huanjin, et al.
Published: (2025)

MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models
by: Zhang, Yichi, et al.
Published: (2024)

Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models
by: Sun, Haoyuan, et al.
Published: (2025)

HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
by: Kang, Zhaolu, et al.
Published: (2025)

TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning
by: Liu, Daixian, et al.
Published: (2026)

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

Cross-modal Information Flow in Multimodal Large Language Models
by: Zhang, Zhi, et al.
Published: (2024)

Gemini in Reasoning: Unveiling Commonsense in Multimodal Large Language Models
by: Wang, Yuqing, et al.
Published: (2023)

Robust Multimodal Large Language Models Against Modality Conflict
by: Zhang, Zongmeng, et al.
Published: (2025)

MLLM-CL: Continual Learning for Multimodal Large Language Models
by: Zhao, Hongbo, et al.
Published: (2025)

Forgotten Polygons: Multimodal Large Language Models are Shape-Blind
by: Rudman, William, et al.
Published: (2025)

Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams
by: Cui, Yiming, et al.
Published: (2025)

BLINK: Multimodal Large Language Models Can See but Not Perceive
by: Fu, Xingyu, et al.
Published: (2024)

Bridging the Missing-Modality Gap: Improving Text-Only Calibration of Vision Language Models
by: Kim, Mingyeong, et al.
Published: (2026)

DirecT2V: Large Language Models are Frame-Level Directors for Zero-Shot Text-to-Video Generation
by: Hong, Susung, et al.
Published: (2023)

Enabling Chatbots with Eyes and Ears: An Immersive Multimodal Conversation System for Dynamic Interactions
by: Jang, Jihyoung, et al.
Published: (2025)

FLEUR: An Explainable Reference-Free Evaluation Metric for Image Captioning Using a Large Multimodal Model
by: Lee, Yebin, et al.
Published: (2024)

Multimodal Retrieval-Augmented Generation with Large Language Models for Medical VQA
by: Karim, A H M Rezaul, et al.
Published: (2025)

LFTR: Learning-Free Token Reduction for Multimodal Large Language Models
by: Zhao, Zihui, et al.
Published: (2025)

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