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cs.LG2026

Modelpedia: A Catalog of Model Findings for the Meta-Science of AI

Franciszek Bernat, Dawid Płudowski, Michał Jan Włodarczyk +6

Scientific knowledge about AI models is produced faster than the community can organize it. Every few months a new foundation model reshapes the field and hundreds of papers, blogs…

cs.CV2026

Your CLIP has 164 dimensions of noise: Exploring the embeddings covariance eigenspectrum of contrastively pretrained vision-language transformers

Jakub Grzywaczewski, Dawid Płudowski, Przemysław 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 Płudowski +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…

cs.LG2026

Trojan horse hunt in deep forecasting models: Insights from the European Space Agency competition

Krzysztof Kotowski, Ramez Shendy, Jakub Nalepa +10

Forecasting plays a crucial role in modern safety-critical applications, such as space operations. However, the increasing use of deep forecasting models introduces a new security…