Efficient Nearest Neighbor Emotion Classification with BERT-whitening
Wenbiao Yin, Lin Shang · 2022
Retrieval-based methods have been proven effective in many NLP tasks.Previous methods use representations from the pre-trained model for similarity search directly.However, the sentence representations from the pre-trained model like BERT perform poorly in retrieving semantically similar sentences, resulting in poor performance of the retrieval-based methods.In this paper, we propose KNN-EC, a simple and efficient non-parametric emotion classification (EC) method using nearest neighbor retrieval.We use BERT-whitening to get better sentence semantics, ensuring that nearest neighbor retrieval works.Meanwhile, BERTwhitening can also reduce memory storage of datastore and accelerate retrieval speed, solving the efficiency problem of the previous methods.KNN-EC average improves the pre-trained model by 1.17 F1-macro on two emotion classification datasets.