数据集:
sileod/movie_recommendation
语言:
en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:
apache-2.0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" }