From the 1 of 15 linked papers with an AI index.
8 papers · 1 filter
VETO: Towards Protecting Images From Frontier AI Editing
Jonas Grebe, Hossein Shakibania, Tobias Braun +2
The paper presents VETO, a subtle anti-edit cloak that disrupts how modern diffusion-based image editors read source images, and introduces VetoBench, a benchmark for evaluating pr…
Obliviate: Erasing Concepts from Autoregressive Image Generation Models
Hossein Shakibania, Jonas Henry Grebe, Tobias Braun +4
The widespread adoption of generative AI models has intensified concerns about misuse, including the creation of unsafe or disturbing imagery. To mitigate such issues, several conc…
SIEVES: Selective Prediction Generalizes through Visual Evidence Scoring
Hector G. Rodriguez, Marcus Rohrbach
Multimodal large language models (MLLMs) achieve ever-stronger performance on visual-language tasks. Even as traditional visual question answering (VQA) benchmarks approach saturat…
Variational Visual Question Answering for Uncertainty-Aware Selective Prediction
Tobias Jan Wieczorek, Nathalie Daun, Mohammad Emtiyaz Khan +1
Despite remarkable progress in recent years, Vision Language Models (VLMs) remain prone to overconfidence and hallucinations on tasks such as Visual Question Answering (VQA) and Vi…
HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models
Reihaneh Zohrabi, Hosein Hasani, Akshita Gupta +3
Large vision-language models can produce object hallucinations in image descriptions, highlighting the need for effective detection and mitigation strategies. Prior work commonly r…
Spurious-Aware Prototype Refinement for Reliable Out-of-Distribution Detection
Reihaneh Zohrabi, Hosein Hasani, Mahdieh Soleymani Baghshah +3
Out-of-distribution (OOD) detection is crucial for ensuring the reliability and safety of machine learning models in real-world applications, where they frequently face data distri…