Unsupervised Natural Language Inference Using PHL Triplet Generation
Unsupervised Natural Language Inference Using PHL Triplet Generation
Transformer-based models achieve impressive performance on numerous Natural Language Inference (NLI) benchmarks when trained on respective training datasets. However, in certain cases, training samples may not be available or collecting them could be time-consuming and resource-intensive. In this work, we address the above challenge and present an explorative study on …