From Colors to Classes: Emergence of Concepts in Vision Transformers
Fuente:
arXiv
Saved in:
| Main Authors: | Dorszewski, Teresa, Tětková, Lenka, Jenssen, Robert, Hansen, Lars Kai, Wickstrøm, Kristoffer Knutsen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Robustness of Visual Explanations to Common Data Augmentation
by: Tětková, Lenka, et al.
Published: (2023)
by: Tětková, Lenka, et al.
Published: (2023)
Keypoint Counting Classifiers: Turning Vision Transformers into Self-Explainable Models Without Training
by: Wickstrøm, Kristoffer, et al.
Published: (2025)
by: Wickstrøm, Kristoffer, et al.
Published: (2025)
Challenges in explaining deep learning models for data with biological variation
by: Tětková, Lenka, et al.
Published: (2024)
by: Tětková, Lenka, et al.
Published: (2024)
Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks
by: Dorszewski, Teresa, et al.
Published: (2024)
by: Dorszewski, Teresa, et al.
Published: (2024)
How Redundant Is the Transformer Stack in Speech Representation Models?
by: Dorszewski, Teresa, et al.
Published: (2024)
by: Dorszewski, Teresa, et al.
Published: (2024)
Mammo-CLIP Dissect: A Framework for Analysing Mammography Concepts in Vision-Language Models
by: Salahuddin, Suaiba Amina, et al.
Published: (2025)
by: Salahuddin, Suaiba Amina, et al.
Published: (2025)
Random Window Augmentations for Deep Learning Robustness in CT and Liver Tumor Segmentation
by: Østmo, Eirik A., et al.
Published: (2025)
by: Østmo, Eirik A., et al.
Published: (2025)
Convexity-based Pruning of Speech Representation Models
by: Dorszewski, Teresa, et al.
Published: (2024)
by: Dorszewski, Teresa, et al.
Published: (2024)
Large Vision Models Can Solve Mental Rotation Problems
by: Mason, Sebastian Ray, et al.
Published: (2025)
by: Mason, Sebastian Ray, et al.
Published: (2025)
Stable Vision Concept Transformers for Medical Diagnosis
by: Hu, Lijie, et al.
Published: (2025)
by: Hu, Lijie, et al.
Published: (2025)
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
by: Trosten, Daniel J., et al.
Published: (2020)
by: Trosten, Daniel J., et al.
Published: (2020)
Supercm: Revisiting Clustering for Semi-Supervised Learning
by: Singh, Durgesh, et al.
Published: (2025)
by: Singh, Durgesh, et al.
Published: (2025)
Class-Discriminative Attention Maps for Vision Transformers
by: Brocki, Lennart, et al.
Published: (2023)
by: Brocki, Lennart, et al.
Published: (2023)
ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers
by: Sinha, Sanchit, et al.
Published: (2025)
by: Sinha, Sanchit, et al.
Published: (2025)
Block Selective Reprogramming for On-device Training of Vision Transformers
by: Sarkar, Sreetama, et al.
Published: (2024)
by: Sarkar, Sreetama, et al.
Published: (2024)
Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
by: Salomonsen, Christian, et al.
Published: (2025)
by: Salomonsen, Christian, et al.
Published: (2025)
The Impact of Longitudinal Mammogram Alignment on Breast Cancer Risk Assessment
by: Thrun, Solveig, et al.
Published: (2025)
by: Thrun, Solveig, et al.
Published: (2025)
In-hoc Concept Representations to Regularise Deep Learning in Medical Imaging
by: Corbetta, Valentina, et al.
Published: (2025)
by: Corbetta, Valentina, et al.
Published: (2025)
From Edges to Depth: Probing the Spatial Hierarchy in Vision Transformers
by: Sanghavi, Jainum
Published: (2026)
by: Sanghavi, Jainum
Published: (2026)
Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers
by: Vielhaben, Johanna, et al.
Published: (2024)
by: Vielhaben, Johanna, et al.
Published: (2024)
CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning
by: Javadi, Amirhosein, et al.
Published: (2026)
by: Javadi, Amirhosein, et al.
Published: (2026)
Vision Transformers Exhibit Human-Like Biases: Evidence of Orientation and Color Selectivity, Categorical Perception, and Phase Transitions
by: Bahador, Nooshin
Published: (2025)
by: Bahador, Nooshin
Published: (2025)
CFM: Language-aligned Concept Foundation Model for Vision
by: Wittenmayer, Kai, et al.
Published: (2026)
by: Wittenmayer, Kai, et al.
Published: (2026)
From Segments to Concepts: Interpretable Image Classification via Concept-Guided Segmentation
by: Eisenberg, Ran, et al.
Published: (2025)
by: Eisenberg, Ran, et al.
Published: (2025)
When Are Concepts Erased From Diffusion Models?
by: Lu, Kevin, et al.
Published: (2025)
by: Lu, Kevin, et al.
Published: (2025)
ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transformer Acceleration
by: Huang, Ning-Chi, et al.
Published: (2024)
by: Huang, Ning-Chi, et al.
Published: (2024)
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
by: Helbling, Alec, et al.
Published: (2025)
by: Helbling, Alec, et al.
Published: (2025)
VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance
by: Srivastava, Divyansh, et al.
Published: (2024)
by: Srivastava, Divyansh, et al.
Published: (2024)
Self-Evolving Visual Concept Library using Vision-Language Critics
by: Sehgal, Atharva, et al.
Published: (2025)
by: Sehgal, Atharva, et al.
Published: (2025)
Native Segmentation Vision Transformers
by: Brasó, Guillem, et al.
Published: (2025)
by: Brasó, Guillem, et al.
Published: (2025)
Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
by: Thrun, Solveig, et al.
Published: (2025)
by: Thrun, Solveig, et al.
Published: (2025)
Vision-Language Models Encode Clinical Guidelines for Concept-Based Medical Reasoning
by: Harmanani, Mohamed, et al.
Published: (2026)
by: Harmanani, Mohamed, et al.
Published: (2026)
Concept-skill Transferability-based Data Selection for Large Vision-Language Models
by: Lee, Jaewoo, et al.
Published: (2024)
by: Lee, Jaewoo, et al.
Published: (2024)
Iwin Transformer: Hierarchical Vision Transformer using Interleaved Windows
by: Huo, Simin, et al.
Published: (2025)
by: Huo, Simin, et al.
Published: (2025)
Matryoshka Query Transformer for Large Vision-Language Models
by: Hu, Wenbo, et al.
Published: (2024)
by: Hu, Wenbo, et al.
Published: (2024)
Slicing Vision Transformer for Flexible Inference
by: Zhang, Yitian, et al.
Published: (2024)
by: Zhang, Yitian, et al.
Published: (2024)
RAViT: Resolution-Adaptive Vision Transformer
by: Guidez, Martial, et al.
Published: (2026)
by: Guidez, Martial, et al.
Published: (2026)
Rotary Position Embedding for Vision Transformer
by: Heo, Byeongho, et al.
Published: (2024)
by: Heo, Byeongho, et al.
Published: (2024)
Decorrelation Speeds Up Vision Transformers
by: Carrigg, Kieran, et al.
Published: (2025)
by: Carrigg, Kieran, et al.
Published: (2025)
ParFormer: A Vision Transformer with Parallel Mixer and Sparse Channel Attention Patch Embedding
by: Setyawan, Novendra, et al.
Published: (2024)
by: Setyawan, Novendra, et al.
Published: (2024)
Similar Items
-
Robustness of Visual Explanations to Common Data Augmentation
by: Tětková, Lenka, et al.
Published: (2023) -
Keypoint Counting Classifiers: Turning Vision Transformers into Self-Explainable Models Without Training
by: Wickstrøm, Kristoffer, et al.
Published: (2025) -
Challenges in explaining deep learning models for data with biological variation
by: Tětková, Lenka, et al.
Published: (2024) -
Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks
by: Dorszewski, Teresa, et al.
Published: (2024) -
How Redundant Is the Transformer Stack in Speech Representation Models?
by: Dorszewski, Teresa, et al.
Published: (2024)