🔗 Who cites «SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness»

60 papers of our library cite it (of the 141,840 whose bibliographies we read) · 3 with a page here, the most cited first · ← back to «SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness»

1. A Survey of Data Augmentation Approaches for NLPSteven Y. Feng, Varun Gangal, Jason Wei, et al.2021 · 937 citations
2. GPT3Mix: Leveraging Large-scale Language Models for Text AugmentationKang Min Yoo, Dongju Park, Jaewook Kang, et al.2021 · 268 citations
3. Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human InterventionsJohn Chung, Ece Kamar, Saleema Amershi2023 · 141 citations

57 more papers of our library cite it; they have no page here yet.

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