The following line will create an .npy encoded representation for the gives wsi with the given model. An optional tissue mask can be specified to speed up ...

Few-shot learning refers to understanding new concepts from only a few examples. We propose an information retrieval-inspired approach for this problem that ...

Retrieval-augmented methods are successful in the standard scenario where the retrieval space is sufficient; whereas in the few-shot scenario with limited ...

A thorough study on how to design and train retrieval-augmented language models, with a focus on downstream few-shot learning and sample efficiency. • The ...

16 авг. 2024 г. · We propose a novel method that adapts DINOv2 and Segment Anything Model 2 (SAM 2) for retrieval-augmented few-shot medical image segmentation.

25 июн. 2024 г. · We exploit a retrieval database to identify relevant demonstrations, and an iterative policy to manage multi-layer hierarchical labels.

In this paper, we suggest to work on Few-shot. Dense Retrieval, a setting where each task comes with a short description and a few examples. To address this, we ...

6 мар. 2024 г. · We present Atlas, a carefully designed and pre-trained retrieval-augmented language model able to learn knowledge intensive tasks with very few training ...

30 дек. 2023 г. · Few-shot image classification is the task of classifying unseen images to one of N mutually exclusive classes, using only a small number of ...

10 дек. 2023 г. · In this paper, we mainly focus on few-shot text classification and retrieve the most helpful examples from the limited training set. 2.2 ...