Crowdsourcing Diverse Paraphrases for Training Task-oriented Bots
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Abstract (arXiv)
A prominent approach to build datasets for training task-oriented bots is crowd-based paraphrasing. Current approaches, however, assume the crowd would naturally provide diverse paraphrases or focus only on lexical diversity. In this WiP we addressed an overlooked aspect of diversity, introducing an approach for guiding the crowdsourcing process towards paraphrases that are syntactically diverse.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 16 references that are in the map. First posted on arXiv 20 Sep 2021.
Builds on
4 of 16 references.
References · 4
- 2018Adversarial Example Generation with Syntactically Controlled Paraphrase Networkscited by 282
- 2020Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversitycited by 35
- 2019Outlier Detection for Improved Data Quality and Diversity in Dialog Systemscited by 28
- 2017Understanding Task Design Trade-offs in Crowdsourced Paraphrase Collectioncited by 3
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Citing papers per year: 2025: 1.
1 paper.