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NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Paraphrase Generation

Paraphrase generation is the task of generating an output sentence that preserves the meaning of the input sentence but contains variations in word choice and grammar. See the example given below:

Input	Output
The need for investors to earn a commercial return may put upward pressure on prices	The need for profit is likely to push up prices

PRANMT-50M

PARANMT-50M dataset is a dataset for training paraphrastic sentence embeddings. It consists of more than 50 million English-English sentential paraphrase pairs.

Model	BLEU	Paper / Source	Code
Trigram (baseline)	47.4	Wieting and Gimpel, 2018	Unavailable
Unsupervised BART w/ Dynamic Blocking	20.9	Niu et al., 2020	Unavailable

QQP-Pos

The QQP-POS dataset is a paraphrase generation dataset with 400K source-target pairs. Each pair is labelled as negative if two questions are not duplicates and positive otherwise.

Model	BLEU	Paper / Source	Code
Unsupervised BART w/ Dynamic Blocking	26.76	Niu et al., 2020	Unavailable
ParafraGPT-UC	35.9	Bui et al., 2020	Code