research
∙
06/09/2023
How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?
Recent large vision-language models such as CLIP have shown remarkable o...
share
research
∙
03/13/2023
Domain Generalization via Nuclear Norm Regularization
The ability to generalize to unseen domains is crucial for machine learn...
research
∙
11/24/2022
Delving into Out-of-Distribution Detection with Vision-Language Representations
Recognizing out-of-distribution (OOD) samples is critical for machine le...
research
∙
06/28/2022
POEM: Out-of-Distribution Detection with Posterior Sampling
Out-of-distribution (OOD) detection is indispensable for machine learnin...
research
∙
05/23/2022
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
Word translation without parallel corpora has become feasible, rivaling ...
research
∙
04/13/2022
Out-of-distribution Detection with Deep Nearest Neighbors
Out-of-distribution (OOD) detection is a critical task for deploying mac...
research
∙
03/17/2022
Are Vision Transformers Robust to Spurious Correlations?
Deep neural networks may be susceptible to learning spurious correlation...
research
∙
03/08/2022
CIDER: Exploiting Hyperspherical Embeddings for Out-of-Distribution Detection
Out-of-distribution (OOD) detection is a critical task for reliable mach...
research
∙
09/12/2021
