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20242026
most citedProvably Robust Multi-bit Watermarking for AI-generated Text

5 citations · 7 across the 20 of their papers we have counts for

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8 papers · 1 filter

cs.LG2025

DMark: Order-Agnostic Watermarking for Diffusion Large Language Models

Linyu Wu, Linhao Zhong, Wenjie Qu +5

Diffusion large language models (dLLMs) offer faster generation than autoregressive models while maintaining comparable quality, but existing watermarking methods fail on them due…

cs.CR2025

RepoMark: A Data-Usage Auditing Framework for Code Large Language Models

Wenjie Qu, Yuguang Zhou, Bo Wang +4

The rapid development of Large Language Models (LLMs) for code generation has transformed software development by automating coding tasks with unprecedented efficiency. However, th…

cs.CR2025

ExtendAttack: Attacking Servers of LRMs via Extending Reasoning

Zhenhao Zhu, Yue Liu, Zhiwei Xu +9

Large Reasoning Models (LRMs) have demonstrated promising performance in complex tasks. However, the resource-consuming reasoning processes may be exploited by attackers to malicio…

cs.CL2025

Efficient Reasoning via Chain of Unconscious Thought

Ruihan Gong, Yue Liu, Wenjie Qu +11

Large Reasoning Models (LRMs) achieve promising performance but compromise token efficiency due to verbose reasoning processes. Unconscious Thought Theory (UTT) posits that complex…

cs.CR2025

Prompt Inversion Attack against Collaborative Inference of Large Language Models

Wenjie Qu, Yuguang Zhou, Yongji Wu +4

Large language models (LLMs) have been widely applied for their remarkable capability of content generation. However, the practical use of open-source LLMs is hindered by high reso…

cs.CR2025

Silent Leaks: Implicit Knowledge Extraction Attack on RAG Systems through Benign Queries

Yuhao Wang, Wenjie Qu, Shengfang Zhai +5

Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by incorporating external knowledge bases, but this may expose them to extraction attacks, leading…

cs.CV2025

Sparse Autoencoder as a Zero-Shot Classifier for Concept Erasing in Text-to-Image Diffusion Models

Zhihua Tian, Sirun Nan, Ming Xu +5

Text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images but also raise people's concerns about generating harmful or misleading con…

cs.CR2025

Efficient Input-level Backdoor Defense on Text-to-Image Synthesis via Neuron Activation Variation

Shengfang Zhai, Jiajun Li, Yue Liu +7

In recent years, text-to-image (T2I) diffusion models have gained significant attention for their ability to generate high quality images reflecting text prompts. However, their gr…