3 citations · 4 across the 12 of their papers we have counts for
15 papers
Discovering Undisclosed Concepts in LoRA Adapters for Diffusion-Based AIGC Models
Yupeng Qiu, Han Fang, Dhananjai Sharma +1
Low-Rank Adaptation (LoRA) has made diffusion model personalization affordable and widely shareable, but it also creates moderation risks when harmful or problematic content is not…
Misleading the Planner through Deceptive Resumes: Registration-Time Injection in Centralized Multi-Agent Systems
Zhaofeng Yu, Haokai Ma, Dongyang Zhan +3
A centralized LLM-based multi-agent system (MAS) extends its functionality by registering new worker agents, whose descriptions are read by the planner to decide how a task is deco…
Autodata: An agentic data scientist to create high quality synthetic data
Ilia Kulikov, Chenxi Whitehouse, Tianhao Wu +12
We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data. We show how to train (meta-optimize) s…
Enhancing Stateful Detection of Adversarial Attacks with Soft-labels' Temporality and Robust Similarity Approximations
De Zhang Lee, Han Fang, Ee-Chien Chang
Stateful Detection (SD) mitigates adversarial attacks by determining whether a sequence of queries contains queries from a black-box adversary. Recent works, such as Blacklight and…
SnapGuard: Lightweight Prompt Injection Detection for Screenshot-Based Web Agents
Mengyao Du, Han Fang, Haokai Ma +4
Web agents have emerged as an effective paradigm for automating interactions with complex web environments, yet remain vulnerable to prompt injection attacks that embed malicious i…
ResetEdit: Precise Text-guided Editing of Generated Image via Resettable Starting Latent
Hanyi Wang, Han Fang, Zheng Wang +2
Recent advances in diffusion models have enabled high-quality image generation, leading to increasing demand for post-generation editing that modifies local regions while preservin…
TrapSuffix: Proactive Defense Against Adversarial Suffixes in Jailbreaking
Mengyao Du, Han Fang, Haokai Ma +4
Suffix-based jailbreak attacks append an adversarial suffix, i.e., a short token sequence, to steer aligned LLMs into unsafe outputs. Since suffixes are free-form text, they admit…
Label Forensics: Interpreting Hard Labels in Black-Box Text Classifier
Mengyao Du, Gang Yang, Han Fang +2
The widespread adoption of natural language processing techniques has led to an unprecedented growth of text classifiers across the modern web. Yet many of these models circulate w…
Removal Attack and Defense on AI-generated Content Latent-based Watermarking
De Zhang Lee, Han Fang, Hanyi Wang +1
Digital watermarks can be embedded into AI-generated content (AIGC) by initializing the generation process with starting points sampled from a secret distribution. When combined wi…
Lie Detector: Unified Backdoor Detection via Cross-Examination Framework
Xuan Wang, Siyuan Liang, Dongping Liao +6
Institutions with limited data and computing resources often outsource model training to third-party providers in a semi-honest setting, assuming adherence to prescribed training p…
Semantic Mirror Jailbreak: Genetic Algorithm Based Jailbreak Prompts Against Open-source LLMs
Xiaoxia Li, Siyuan Liang, Jiyi Zhang +3
Large Language Models (LLMs), used in creative writing, code generation, and translation, generate text based on input sequences but are vulnerable to jailbreak attacks, where craf…
Domain Bridge: Generative model-based domain forensic for black-box models
Jiyi Zhang, Han Fang, Ee-Chien Chang
In forensic investigations of machine learning models, techniques that determine a model's data domain play an essential role, with prior work relying on large-scale corpora like I…
Adaptive Attractors: A Defense Strategy against ML Adversarial Collusion Attacks
Jiyi Zhang, Han Fang, Ee-Chien Chang
In the seller-buyer setting on machine learning models, the seller generates different copies based on the original model and distributes them to different buyers, such that advers…
Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation
Jiyi Zhang, Han Fang, Hwee Kuan Lee +1
Given a poorly documented neural network model, we take the perspective of a forensic investigator who wants to find out the model's data domain (e.g. whether on face images or tra…
Mitigating Adversarial Attacks by Distributing Different Copies to Different Users
Jiyi Zhang, Han Fang, Wesley Joon-Wie Tann +3
Machine learning models are vulnerable to adversarial attacks. In this paper, we consider the scenario where a model is distributed to multiple buyers, among which a malicious buye…