SentEval
Related Papers
SentEval: An Evaluation Toolkit for Universal Sentence Representations
We introduce SentEval, a toolkit for evaluating the quality of universal sentence representations. SentEval encompasses a variety of tasks, including binary and multi-class classification, natural language inference and sentence similarity. …...
DisSent: Learning Sentence Representations from Explicit Discourse Relations
AbstractLearning effective representations of sentences is one of the core missions of natural language understanding. Existing models either train on a vast amount of text, or require costly, manually curated …...
Is Language Modeling Enough? Evaluating Effective Embedding Combinations
AbstractUniversal embeddings, such as BERT or ELMo, are useful for a broad set of natural language processing tasks like text classification or sentiment analysis. Moreover, specialized embeddings also exist for …...
A Contrastive Framework for Learning Sentence Representations from Pairwise and Triple-wise Perspective in Angular Space
AbstractLearning high-quality sentence representations is a fundamental problem of natural language processing which could benefit a wide range of downstream tasks. Though the BERT-like pre-trained language models have achieved great …...