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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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13 papers · 1 filter

cs.CR2026

Practical Secrets Extraction against Black-box LLMs

Shiqian Zhao, Siwei Jiang, Xinfeng Li +5

Large language models (LLMs) increasingly power autonomous coding agents such as Codex and Claude Code, yet their training corpora may contain confidential credentials exposed in p…

cs.CR2026

Beyond Over-Refusal: Defending Indirect Prompt Injection via Latent Instruction Manifolds

Jiahao Chen, Rui Yin, Xinfeng Li +6

Large Language Models (LLMs) have been integrated into complex ecosystems (e.g., Code Agents), while Indirect Prompt Injection (IPI) attacks have emerged as critical barriers to th…

cs.CL2026

ICO: Enhancing Semantic-Shift Jailbreaks via Iterative Context Optimization

Hujian Zhu, Yihao Huang, Felix Juefei-Xu +5

Foundation models have achieved remarkable success across diverse tasks, but they remain vulnerable. To investigate such vulnerabilities, semantic-shift jailbreaks have recently em…

cs.CR2026

Understanding Implicit Trust Errors in Core Carrier Networks through Multi-Agent Flaw Discovery and Analysis

Ziyu Lin, Ziting Wang, Xinfeng Li +2

Cellular core networks (CNs) are critical infrastructure, yet their internal security model has historically relied on physical isolation: interfaces between core components often…

cs.CR2026

Customization under Fire: Plugin Poisoning in Text-to-Image Ecosystem

Jiahao Chen, Xing He, Yong Yang +6

The prosperity of text-to-image (T2I) models has fostered a vibrant share-and-play ecosystem centered on Low-Rank Adaptation (LoRA) plugins, which allow users to customize and shar…

cs.AI2026

AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters

Hanjun Luo, Zhimu Huang, Sylvia Chung +6

Text-to-image (T2I) systems increasingly rely on upstream prompters, either humans or multimodal large language models (MLLMs), to translate user intent into detailed prompts. Yet…

cs.SD2026

A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook

Kaiwen Luo, Zhenhong Zhou, Leyan Wang +32

Advances in Large Language Models (LLMs) have paved the way for Multimodal Large Language Models (MLLMs). Among these, Large Audio Language Models (LALMs) are essential for realizi…

cs.CY2026

BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models

Hanjun Luo, Zhimu Huang, Haoyu Huang +5

Text-to-Image (T2I) generative models have revolutionized content creation, yet they inherently risk amplifying societal biases. While sociological research provides systematic cla…

cs.CR2026

You Told Me to Do It: Measuring Instructional Text-induced Private Data Leakage in LLM Agents

Ching-Yu Kao, Xinfeng Li, Shenyu Dai +4

High-privilege LLM agents that autonomously process external documentation are increasingly trusted to automate tasks by reading and executing project instructions, yet they are gr…

cs.HC2026

"Are You Sure?": An Empirical Study of Human Perception Vulnerability in LLM-Driven Agentic Systems

Xinfeng Li, Shenyu Dai, Kelong Zheng +4

Large language model (LLM) agents are rapidly becoming trusted copilots in high-stakes domains like software development and healthcare. However, this deepening trust introduces a…

cs.CR2026

The Landscape of Prompt Injection Threats in LLM Agents: From Taxonomy to Analysis

Peiran Wang, Xinfeng Li, Chong Xiang +5

The evolution of Large Language Models (LLMs) has resulted in a paradigm shift towards autonomous agents, necessitating robust security against Prompt Injection (PI) vulnerabilitie…

cs.CL2026

MVSS: A Unified Framework for Multi-View Structured Survey Generation

Yinqi Liu, Yueqi Zhu, Yongkang Zhang +7

Scientific surveys require not only summarizing large bodies of literature, but also organizing them into clear and coherent conceptual structures. However, existing automatic surv…

cs.CR2026

DP-MGTD: Privacy-Preserving Machine-Generated Text Detection via Adaptive Differentially Private Entity Sanitization

Lionel Z. Wang, Yusheng Zhao, Jiabin Luo +6

The deployment of Machine-Generated Text (MGT) detection systems necessitates processing sensitive user data, creating a fundamental conflict between authorship verification and pr…