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sebastianruder / 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.
https://nlpprogress.com/
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Update paraphrase-generation.md #626

Closed adrienpayong closed 3 months ago

adrienpayong commented 1 year ago

MULTIPIT, MULTIPITCROWD and MULTIPITEXPERT

Past efforts on creating paraphrase corpora only consider one paraphrase criteria without taking into account the fact that the desired “strictness” of semantic equivalence in paraphrases varies from task to task (Bhagat and Hovy, 2013; Liu and Soh, 2022). For example, for the purpose of tracking unfolding events, “A tsunami hit Haiti.” and “303 people died because of the tsunami in Haiti” are sufficiently close to be considered as paraphrases; whereas for paraphrase generation, the extra information “303 people dead” in the latter sentence may lead models to learn to hallucinate and generate more unfaithful content. In this paper, the authors present an effective data collection and annotation method to address these issues.

MULTIPIT is a topic Paraphrase in Twitter corpus that consists of a total of 130k sentence pairs with crowdsoursing (MULTIPITCROWD ) and expert (MULTIPITEXPERT ) annotations. MULTIPITCROWD is a large crowdsourced set of 125K sentence pairs that is useful for tracking information onTwitter. Model F1 Paper / Source Code
DeBERTaV3large 92.00 Improving Large-scale Paraphrase Acquisition and Generation Unavailable
MULTIPITEXPERT is an expert annotated set of 5.5K sentence pairs using a stricter definition that is more suitable for acquiring paraphrases for generation purpose. Model F1 Paper / Source Code
DeBERTaV3large 83.20 Improving Large-scale Paraphrase Acquisition and Generation Unavailable
sebastianruder commented 3 months ago

Thanks for adding this paraphrase corpus! 👍