Update paraphrase-generation.md

[adrienpayong]

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