--- title: "Who cites StructBERT: Incorporating — 84 citing papers" description: "84 papers of the Elamur Research library cite «StructBERT: Incorporating Language Structures into Pre-training for Deep Language…" canonical: "https://research.elamur.ai/free/en/papers/wang-2019-structbert-incorporating-language-structures-pre/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2019-structbert-incorporating-language-structures-pre/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [StructBERT: Incorporating Language Structures…](https://md.research.elamur.ai/free/en/papers/wang-2019-structbert-incorporating-language-structures-pre/) / cited by # Who cites «StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding» 84 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding»](https://md.research.elamur.ai/free/en/papers/wang-2019-structbert-incorporating-language-structures-pre/) 1. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 11,325 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/) 2. [**ALBERT: A Lite BERT for Self-supervised Learning of Language Representations arXiv:1909.11942**Zhenzhong Lan, Mingda Chen, Sebastian Goodman, et al.*2019 · 2,806 citations*](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/) 3. [**DeBERTa: Decoding-enhanced BERT with Disentangled Attention arXiv:2006.03654**Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 1,828 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/) 4. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/) 5. **[SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoming Jiang, Pengcheng He, Weizhu Chen, et al.*2020 · 304 citations* 6. [**E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT arXiv:1911.03681**Nina Poerner, Ulli Waltinger, Hinrich Schutze*2019 · 247 citations*](https://md.research.elamur.ai/free/en/papers/poerner-2019-e-bert-efficient-yet-effective/) 7. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining arXiv:2102.08473**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 198 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/) 8. **[Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ma-2022-linguistic-rules-based-corpus-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shirong Ma, Yinghui Li, Rongyi Sun, et al.*2022 · 59 citations* 9. **[CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis](https://md.research.elamur.ai/free/en/papers/xu-2026-cnsocialdepress-chinese-social-media-dataset/) [Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium](https://md.research.elamur.ai/free/en/venues/rapid/)**Jinyuan Xu, Tian Lan, Xintao Yu, et al.*2026* 10. **[LoRE: Enhancing Search Relevance with Progressive Chain-of-Thought and Preference Alignment](https://md.research.elamur.ai/free/en/papers/lu-2026-lore-enhancing-search-relevance-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenji Lu, Zhuo Chen, Hui Zhao, et al.*2026* 74 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2019-structbert-incorporating-language-structures-pre/) — StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding