Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots
cs.RO, cs.AI, cs.CY
Submitted: 2024-12-21
Updated: 2026-10-01
Project page: https://poex-jailbreak.github.io/Abstract
Terminology
Sources
- GPT-4 Technical Report
- Gemini: A Family of Highly Capable Multimodal Models
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- The Llama 3 Herd of Models
- Qwen2.5 Technical Report
- Gemma 2: Improving Open Language Models at a Practical Size
- Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
- ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
- Yi: Open Foundation Models by 01.AI
- Baichuan 2: Open Large-scale Language Models
- Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI
- Universal and Transferable Adversarial Attacks on Aligned Language Models
- Jailbreaking Black Box Large Language Models in Twenty Queries
- Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
- GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
- Safety Assessment of Chinese Large Language Models
- HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
- JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
- DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding
- Fast Segment Anything
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