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20232026
most citedSafeGen: Mitigating Sexually Explicit Content Generation in Text-to-Image Models

19 citations · 48 across the 48 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.RO2024

Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots

Xuancun Lu, Zhengxian Huang, Xinfeng Li +4

LLM-based robots use Large Language Models (LLMs) as planners to translate natural language instructions into policies such as grasp(), move_to(), and open_gripper(). Jailbreak att…

cs.CR2024★ 1 cited

Heuristic-Induced Multimodal Risk Distribution Jailbreak Attack for Multimodal Large Language Models

Ma Teng, Jia Xiaojun, Duan Ranjie +5

With the rapid advancement of multimodal large language models (MLLMs), concerns regarding their security have increasingly captured the attention of both academia and industry. Al…

cs.CR2024★ 1 cited

SafeEar: Content Privacy-Preserving Audio Deepfake Detection

Xinfeng Li, Kai Li, Yifan Zheng +3

Text-to-Speech (TTS) and Voice Conversion (VC) models have exhibited remarkable performance in generating realistic and natural audio. However, their dark side, audio deepfake pose…

cs.CL2024

RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation

Xuanwang Zhang, Yunze Song, Yidong Wang +10

Large Language Models (LLMs) demonstrate human-level capabilities in dialogue, reasoning, and knowledge retention. However, even the most advanced LLMs face challenges such as hall…

cs.CL2024★ 1 cited

Legilimens: Practical and Unified Content Moderation for Large Language Model Services

Jialin Wu, Jiangyi Deng, Shengyuan Pang +4

Given the societal impact of unsafe content generated by large language models (LLMs), ensuring that LLM services comply with safety standards is a crucial concern for LLM service…

cs.CR2024★ 2 cited

RACONTEUR: A Knowledgeable, Insightful, and Portable LLM-Powered Shell Command Explainer

Jiangyi Deng, Xinfeng Li, Yanjiao Chen +5

Malicious shell commands are linchpins to many cyber-attacks, but may not be easy to understand by security analysts due to complicated and often disguised code structures. Advance…

cs.CV2024★ 19 cited

SafeGen: Mitigating Sexually Explicit Content Generation in Text-to-Image Models

Xinfeng Li, Yuchen Yang, Jiangyi Deng +4

Text-to-image (T2I) models, such as Stable Diffusion, have exhibited remarkable performance in generating high-quality images from text descriptions in recent years. However, text-…