Cover Image

Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Crabbé, Jonathan, Rodríguez, Pau, Shankar, Vaishaal, Zappella, Luca, Blaas, Arno
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fine-Grained ImageNet Classification in the Wild
by: Lymperaiou, Maria, et al.
Published: (2023)

Automated Classification of Model Errors on ImageNet
by: Peychev, Momchil, et al.
Published: (2023)

ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object
by: Zhang, Chenshuang, et al.
Published: (2024)

Controlling Language and Diffusion Models by Transporting Activations
by: Rodriguez, Pau, et al.
Published: (2024)

Can Biases in ImageNet Models Explain Generalization?
by: Gavrikov, Paul, et al.
Published: (2024)

Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification
by: Dahal, Ashim, et al.
Published: (2025)

Mitigating Overfitting in Medical Imaging: Self-Supervised Pretraining vs. ImageNet Transfer Learning for Dermatological Diagnosis
by: Matas, Iván, et al.
Published: (2025)

Accessing Vision Foundation Models via ImageNet-1K
by: Zhang, Yitian, et al.
Published: (2024)

MobileCLIP2: Improving Multi-Modal Reinforced Training
by: Faghri, Fartash, et al.
Published: (2025)

Transfer Learning from ImageNet for MEG-Based Decoding of Imagined Speech
by: Jhilal, Soufiane, et al.
Published: (2026)

Scaling Up Deep Clustering Methods Beyond ImageNet-1K
by: Adaloglou, Nikolas, et al.
Published: (2024)

Interpreting ResNet-based CLIP via Neuron-Attention Decomposition
by: Bu, Edmund, et al.
Published: (2025)

From MNIST to ImageNet: Understanding the Scalability Boundaries of Differentiable Logic Gate Networks
by: Brändle, Sven, et al.
Published: (2025)

Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
by: Yin, Zeyuan, et al.
Published: (2023)

Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation
by: Zhang, Yuhui, et al.
Published: (2023)

Interpreting CLIP's Image Representation via Text-Based Decomposition
by: Gandelsman, Yossi, et al.
Published: (2023)

Self-supervised Benchmark Lottery on ImageNet: Do Marginal Improvements Translate to Improvements on Similar Datasets?
by: Ozbulak, Utku, et al.
Published: (2025)

ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
by: Burgert, Tom, et al.
Published: (2025)

Quantifying and Enabling the Interpretability of CLIP-like Models
by: Madasu, Avinash, et al.
Published: (2024)

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
by: Vishniakov, Kirill, et al.
Published: (2023)

Video CLIP Model for Multi-View Echocardiography Interpretation
by: Takizawa, Ryo, et al.
Published: (2025)

Speedrunning ImageNet Diffusion
by: Bhanded, Swayam
Published: (2025)

LinEAS: End-to-end Learning of Activation Steering with a Distributional Loss
by: Rodriguez, Pau, et al.
Published: (2025)

RadCLIP: Enhancing Radiologic Image Analysis through Contrastive Language-Image Pre-training
by: Lu, Zhixiu, et al.
Published: (2024)

Occlusion Robustness of CLIP for Military Vehicle Classification
by: van Woerden, Jan Erik, et al.
Published: (2025)

Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains
by: Baek, Eunsu, et al.
Published: (2024)

Interpreting CLIP with Hierarchical Sparse Autoencoders
by: Zaigrajew, Vladimir, et al.
Published: (2025)

Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNet
by: Giulivi, Loris, et al.
Published: (2024)

CLIP-DQA: Blindly Evaluating Dehazed Images from Global and Local Perspectives Using CLIP
by: Zeng, Yirui, et al.
Published: (2025)

FoCLIP: A Feature-Space Misalignment Framework for CLIP-Based Image Manipulation and Detection
by: Chen, Yulin, et al.
Published: (2025)

ProtoArgNet: Interpretable Image Classification with Super-Prototypes and Argumentation [Technical Report]
by: Ayoobi, Hamed, et al.
Published: (2023)

ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
by: Yang, William, et al.
Published: (2023)

microCLIP: Unsupervised CLIP Adaptation via Coarse-Fine Token Fusion for Fine-Grained Image Classification
by: Silva, Sathira, et al.
Published: (2025)

Investigating the Semantic Robustness of CLIP-based Zero-Shot Anomaly Segmentation
by: Stangl, Kevin, et al.
Published: (2024)

Team NYCU at Defactify4: Robust Detection and Source Identification of AI-Generated Images Using CNN and CLIP-Based Models
by: Yang, Tsan-Tsung, et al.
Published: (2025)

GAFR-Net: A Graph Attention and Fuzzy-Rule Network for Interpretable Breast Cancer Image Classification
by: Gao, Lin-Guo, et al.
Published: (2026)

Knowledge-Base based Semantic Image Transmission Using CLIP
by: Li, Chongyang, et al.
Published: (2025)

Enhancing Multimodal Understanding with CLIP-Based Image-to-Text Transformation
by: Che, Chang, et al.
Published: (2024)

A Comparative Study of Adversarial Robustness in CNN and CNN-ANFIS Architectures
by: Shankar, Kaaustaaub, et al.
Published: (2026)

Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition
by: Luo, Róisín, et al.
Published: (2024)