5 papers
MMD Guidance: Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
Matina Mahdizadeh Sani, Nima Jamali, Mohammad Jalali +1
Pre-trained diffusion models have emerged as powerful generative priors for both unconditional and conditional sample generation, yet their outputs often deviate from the character…
The CIFAR Synthetic Evidence Corpus for Detecting AI-Generated Evidence
Kelly McConvey, Jalehsadat Mahdavimoghaddam, Nima Jamali +8
The growing ability of generative models to produce realistic documents poses a direct challenge to evidentiary workflows in the justice system and the courts, where decisions incr…
DetectZoo: A Unified Toolkit for AI-Generated Content Detection Across Text, Audio, and Image Modalities
Sajad Ebrahimi, Nima Jamali, Bardia Shirsalimian +8
The growing popularity and capacity of generative models have eroded the distinction between human and machine-generated content, motivating a growing body of work on detection acr…
ImagenWorld: Stress-Testing Image Generation Models with Explainable Human Evaluation on Open-ended Real-World Tasks
Samin Mahdizadeh Sani, Max Ku, Nima Jamali +23
Advances in diffusion, autoregressive, and hybrid models have enabled high-quality image synthesis for tasks such as text-to-image, editing, and reference-guided composition. Yet,…
KNN-Defense: Defense against 3D Adversarial Point Clouds using Nearest-Neighbor Search
Nima Jamali, Matina Mahdizadeh Sani, Hanieh Naderi +1
Deep neural networks (DNNs) have demonstrated remarkable performance in analyzing 3D point cloud data. However, their vulnerability to adversarial attacks-such as point dropping, s…