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20242026
most citedFairness Mediator: Neutralize Stereotype Associations to Mitigate Bias in Large Language Models

3 citations · 7 across the 41 of their papers we have counts for

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cs.CV2026

CIVA: Critic-Induced Value-Subspace Attacks on Visual World-Model Agents

Jiancheng Wang, Mingli Zhu, Tong Zhang +4

Visual world-model agents such as DreamerV3 act through a recurrent latent state rather than a single observation, which weakens frame-wise observation attacks and makes their pert…

cs.CV2026

SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense

Siyuan Liang, Yupeng Qiu, Junfeng Fang +3

Text-to-Video (T2V) generative models are vulnerable to jailbreak attacks in real-world deployment, leading them to produce harmful or inappropriate content. Existing defense appro…

cs.CV2026

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective

Tianyuan Zhang, Xianglong Liu, Aishan Liu +6

Environmental illusions (eg., shadows, reflections, and tire marks) are naturally existing yet overlooked phenomena in real-world driving environments. They can disturb visual perc…

cs.CV2026

Who Generated This 3D Asset? Learning Source Attribution for Generative 3D Models

Sihan Ma, Siyuan Liang, Dacheng Tao

Generative 3D models are deployed in gaming, robotics, and immersive creation, making source attribution critical: given a 3D asset, can we identify whether and which generative mo…

cs.CV2026

CtrlAttack: A Unified Attack on World-Model Control in Diffusion Models

Shuhan Xu, Siyuan Liang, Hongling Zheng +4

Diffusion-based image-to-video (I2V) models increasingly exhibit world-model-like properties by implicitly capturing temporal dynamics. However, existing studies have mainly focuse…

cs.CV2025

Review of Hallucination Understanding in Large Language and Vision Models

Zhengyi Ho, Siyuan Liang, Dacheng Tao

The widespread adoption of large language and vision models in real-world applications has made urgent the need to address hallucinations -- instances where models produce incorrec…