数据集:
sileod/movie_recommendation
语言:
计算机处理:
monolingual大小:
n<1K语言创建人:
crowdsourced批注创建人:
expert-generated源数据集:
original数字对象标识符:
10.57967/hf/0257许可:
我们证明了预训练的大型语言模型可以作为一个推荐系统,并将少样本学习结果与矩阵分解基准进行比较。这是我们基于语言的电影推荐数据集的BIG-Bench版本。
https://github.com/google/BIG-bench/tree/main/bigbench/benchmark_tasks/movie_recommendation
GPT-2的准确率为48.8%,概率为25%。人类准确率为60.4%。
@InProceedings{sileodreclm22,
author="Sileo, Damien
and Vossen, Wout
and Raymaekers, Robbe",
editor="Hagen, Matthias
and Verberne, Suzan
and Macdonald, Craig
and Seifert, Christin
and Balog, Krisztian
and N{\o}rv{\aa}g, Kjetil
and Setty, Vinay",
title="Zero-Shot Recommendation as Language Modeling",
booktitle="Advances in Information Retrieval",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="223--230",
isbn="978-3-030-99739-7"
}