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20242026
most citedMIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense

2 citations · 2 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Closing the Safety Gap: Surgical Concept Erasure in Visual Autoregressive Models

Xinhao Zhong, Yimin Zhou, Zhiqi Zhang +6

The rapid progress of visual autoregressive (VAR) models has brought new opportunities for text-to-image generation, but also heightened safety concerns. Existing concept erasure t…

cs.CV2025

Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization

Yixiang Qiu, Yanhan Liu, Hongyao Yu +4

The growing complexity of Deep Neural Networks (DNNs) has led to the adoption of Split Inference (SI), a collaborative paradigm that partitions computation between edge devices and…

cs.CL2025

Emergent Hierarchical Structure in Large Language Models: An Information-Theoretic Framework for Multi-Scale Representation

Yukin Zhang, Qi Dong, Kemu Xu

Why do language models from different architecture families respond so differently to the same perturbation? We argue that the answer is not scale, but \emph{how architecture shape…

cs.CL2025

Revisiting Backdoor Attacks on LLMs: A Stealthy and Practical Poisoning Framework via Harmless Inputs

Jiawei Kong, Hao Fang, Xiaochen Yang +5

Recent studies have widely investigated backdoor attacks on Large Language Models (LLMs) by inserting harmful question-answer (QA) pairs into their training data. However, we revis…

cs.CV2025

Neural Antidote: Class-Wise Prompt Tuning for Purifying Backdoors in CLIP

Jiawei Kong, Hao Fang, Sihang Guo +5

While pre-trained Vision-Language Models (VLMs) such as CLIP exhibit impressive representational capabilities for multimodal data, recent studies have revealed their vulnerability…