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20242026
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cs.CV2026

ALLUDE: A Unified Evaluation System for Configurable Attacks in Differentiable Environments

Mansi Phute, Alexander Greenhalgh, Matthew Hull +8

Adversarial attacks against vision models like object detectors are often evaluated under limited conditions, leaving their performance under-characterized. Bridging simulation and…

cs.CV2026

VISOR++: Universal Visual Inputs based Steering for Large Vision Language Models

Ravikumar Balakrishnan, Mansi Phute

As Vision Language Models (VLMs) are deployed across safety-critical applications, understanding and controlling their behavioral patterns has become increasingly important. Existi…

cs.CV2026

VISOR: Visual Input-based Steering for Output Redirection in Vision-Language Models

Mansi Phute, Ravikumar Balakrishnan

Vision Language Models (VLMs) are increasingly being used in a broad range of applications, bringing their security and behavioral control to the forefront. While existing approach…

cs.CV2025

ComplicitSplat: Downstream Models are Vulnerable to Blackbox Attacks by 3D Gaussian Splat Camouflages

Matthew Hull, Haoyang Yang, Pratham Mehta +8

As 3D Gaussian Splatting (3DGS) gains rapid adoption in safety-critical tasks for efficient novel-view synthesis from static images, how might an adversary tamper images to cause h…

cs.CV2024

Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors

Anisha Pal, Julia Kruk, Mansi Phute +4

Text-to-image diffusion models have impactful applications in art, design, and entertainment, yet these technologies also pose significant risks by enabling the creation and dissem…