2 papers
cs.CV2026
Hierarchical Prompt Learning for Hyperbolic Vision-Language Models
Andro Erdelez, Pascal Mettes, Behzad Bozorgtabar
Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstream tasks has largely relied…
cs.CV2025
[Re] Improving Interpretation Faithfulness for Vision Transformers
Izabela Kurek, Wojciech Trejter, Stipe Frkovic +1
This work aims to reproduce the results of Faithful Vision Transformers (FViTs) proposed by arXiv:2311.17983 alongside interpretability methods for Vision Transformers from arXiv:2…