17 citations · 20 across the 23 of their papers we have counts for
8 papers · 1 filter
D-Scope: Decomposing and Steering Diffusion Transformers with Sparse Autoencoders
Xinyue Xu, Jiahao Zhang, Lijie Hu +2
Sparse autoencoders (SAEs) reveal visual structure in diffusion transformers (DiTs), but interpreting a feature does not establish whether it can be used to control generation. We…
CleanVideo: Adaptive Concept Erasure for Text-to-Video Diffusion Models
Junchi Liao, Hongji Li, Wenrui Zhou +1
Concept erasure aims to selectively eliminate undesired visual semantics from pre-trained generative models without compromising their general utility. Extending concept erasure fr…
Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model
Yijun Yang, Ruiqiang Xiao, Lijie Hu +4
Deep learning has revolutionized medical image analysis, delivering exceptional diagnostic accuracy across diverse applications. Yet, the lack of interpretability in its decision-m…
Bayesian Gated Non-Negative Contrastive Learning
Peng Cui, Jiahao Zhang, Lijie Hu
While Contrastive Learning (CL) has revolutionized self-supervised representation learning, its latent representations remain highly entangled and opaque, limiting their interpreta…
MedFM-Robust: Benchmarking Robustness of Medical Foundation Models
Xiangxiang Cui, Tianjin Huang, Yifang Wang +2
Medical foundation models have achieved remarkable clinical performance, yet their robustness under real-world perturbations remains underexplored. We present a robustness benchmar…
Visual Self-Fulfilling Alignment: Shaping Safety-Oriented Personas via Threat-Related Images
Qishun Yang, Shu Yang, Lijie Hu +1
Multimodal large language models (MLLMs) face safety misalignment, where visual inputs enable harmful outputs. To address this, existing methods require explicit safety labels or c…
Backdooring Vision-Language Models with Out-Of-Distribution Data
Weimin Lyu, Jiachen Yao, Saumya Gupta +6
The emergence of Vision-Language Models (VLMs) represents a significant advancement in integrating computer vision with Large Language Models (LLMs) to generate detailed text descr…
SATO: Stable Text-to-Motion Framework
Wenshuo Chen, Hongru Xiao, Erhang Zhang +4
Is the Text to Motion model robust? Recent advancements in Text to Motion models primarily stem from more accurate predictions of specific actions. However, the text modality typic…