FEW-SHOT TEXT CLASSIFICATION WITH DISTRIBUTIONAL SIGNATURES
任务
Given an N-way K-shot classification task
论文设计图像
数据集
20 Newsgroups is comprised of informal discourse from news discussion forums (Lang, 1995).Documents are organized under 20 topics.
RCV1 is a collection of Reuters newswire articles from 1996 to 1997 (Lewis et al., 2004). These articles are written in formal speech and labeled with a set of topic codes. We consider 71 secondlevel topics as our total class set and discard articles that belong to more than one class.
Reuters-21578 is a collection of shorter Reuters articles from 1987 (Lewis, 1997). We use the standard ApteMod version of the dataset. We discard articles with more than one label and consider 31 classes that have at least 20 articles. *** Amazon product data** contains customer reviews from 24 product categories (He & McAuley, 2016). Our goal is to classify reviews into their respective product categories. Since the original dataset is notoriously large (142.8 million reviews), we select a more tractable subset by sampling 1000 reviews from each category.
HuffPost headlines consists of news headlines published on HuffPost between 2012 and 2018 (Misra, 2018). These headlines split among 41 classes. They are shorter and less grammatical than formal sentences.
FewRel is a relation classification dataset developed for few-shot learning (Han et al., 2018). Each example is a single sentence, annotated with a head entity, a tail entity, and their relation. The goal is to predict the correct relation between the head and tail. The public dataset contains 80 relation types.
Baselines
Representations
AVG
IDF
CNN
Learning algorithms
the ridge regressor (RR)
Prototypical network (PROTO)
FT pre-trains a classifier
MAML
NN
biLSTM
执行细节
pre-trained fastText embeddings
sentence-level datasets (HuffPost, FewRel)
pre-trained BERT embeddings using HuggingFaces codebase
a biLSTM with 50 hidden units and apply dropout of 0.1
In the ridge regressor
Adam
early stopping
1000
testing episodes
the average accuracy over 5 different random seeds.
5-way 1-shot and 5-way 5-shot classification
操作
Ablation study
Contextualized representations
PCA visualization of the input representation for the query set of a testing episode