SufiSent - Universal Sentence Representations Using Suffix Encodings
Computing universal distributed representations of sentences is a fundamental task in natural language processing. We propose a method to learn such representations by encoding the suffixes of word sequences in a sentence and training on the Stanford Natural Language Inference (SNLI) dataset. We demonstrate the effectiveness of our approach by evaluating it on the SentEval benchmark, improving on existing approaches on several transfer tasks.
PDF AbstractDatasets
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here