---
title: "Who cites ERNIE-GEN: An Enhanced — 42 citing papers"
description: "42 papers of the Elamur Research library cite «ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural…"
canonical: "https://research.elamur.ai/free/en/papers/xiao-2020-ernie-gen-enhanced-multi/cited-by/"
---
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# Who cites «ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation»

42 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 «ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation»](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gen-enhanced-multi/)

1. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2107.02137**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 328 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
2. **[UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning](https://md.research.elamur.ai/free/en/papers/li-2021-unimo-unified-modal-understanding-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Li, Can Gao, Guocheng Niu, et al.*2021 · 299 citations*
3. **[BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/asai-2024-buffet-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.*2024 · 85 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gen-enhanced-multi/) — ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation