Showing cs.CVShow all
3 papers · 1 filter
cs.CV2026
Your CLIP has 164 dimensions of noise: Exploring the embeddings covariance eigenspectrum of contrastively pretrained vision-language transformers
Jakub Grzywaczewski, Dawid PÅudowski, PrzemysÅaw Biecek
Contrastively pre-trained Vision-Language Models (VLMs) serve as powerful feature extractors. Yet, their shared latent spaces are prone to structural anomalies and act as repositor…
cs.CV2026
SwordBench: Evaluating Orthogonality of Steering Image Representations
Vladimir Zaigrajew, Dawid Pludowski, Hubert Baniecki +1
Steering or intervening on model representations at inference time to correct predictions is essential for AI interpretability and safety, yet existing evaluation protocols are lim…
cs.CV2026
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
Bartlomiej Sobieski, Matthew Tivnan, Dawid PÅudowski +4
Diffusion models are prone to generating structural hallucinations - samples that match the statistical properties of the training data yet defy underlying structural rules, result…