Autoencoder Paraphrase Dataset (AEPD)

홈페이지 · 논문 1편

This is a benchmark for neural paraphrase detection, to differentiate between original and machine-generated content. ####Training: 1,474,230 aligned paragraphs (98,282 original, 1,375,948 paraphrased with 3 models and 5 hyperparameter configurations each 98,282) extracted from 4,012 (English) Wikipedia articles. ####Testing: `` BERT-large (cased): arXiv - Original - 20,966; Paraphrased - 20,966; Theses - Original - 5,226; Paraphrased - 5,226; Wikipedia - Original - 39,241; Paraphrased - 39,241; RoBERTa-large (cased): arXiv - Original - 20,966; Paraphrased - 20,966; Theses - Original - 5,226; Paraphrased - 5,226; Wikipedia - Original - 39,241; Paraphrased - 39,241; Longformer-large (uncased): arXiv - Original - 20,966; Paraphrased - 20,966; Theses - Original - 5,226; Paraphrased - 5,226; Wikipedia - Original - 39,241; Paraphrased - 39,241; ``