5 авг. 2022 г. · A carefully designed and pre-trained retrieval augmented language model able to learn knowledge intensive tasks with very few training examples.

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 ...

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 ...

16 нояб. 2022 г. · In this work we address this gap, and present Atlas, a retrieval-augmented language model capable of strong few-shot learning, despite having ...

In this work we present Atlas, a carefully designed and pre-trained retrieval augmented language model able to learn knowledge intensive tasks with very few ...

This repository contains pre-trained models, corpora, indices, and code for pre-training, finetuning, retrieving and evaluating for the paper Atlas: Few-shot ...

Large language models have shown impressive few-shot results on a wide range of tasks. However, when knowledge is key for such results, as is the case for tasks ...

5 авг. 2022 г. · This work presents Atlas, a carefully designed and pre-trained retrieval augmented language model able to learn knowledge intensive tasks ...

Продолжительность: 15:01
Опубликовано: 9 июл. 2023 г.

Atlas is a retrieval-augmented language model pretrained on unlabeled data that exhibits few-shot abilities on knowledge-intensive tasks, such as Q&A and fact- ...