Seeds: Sampling-Enhanced Embeddings.

Finding a desirable sampling estimator has a profound impact on the development of static word embedding models, such as continue-bag-of-words (CBOW) and skip gram (SG), which have been generally accepted as popular low-resource algorithms to generate task-agnostic word representations. Due to the prevalence of large-scale pretrained models, less attention has been paid to these static models in the recent years. However, compared with the dynamic embedding models (e.