--- title: "Who cites Transformers without Tears: — 73 citing papers" description: "73 papers of the Elamur Research library cite «Transformers without Tears: Improving the Normalization of Self-Attention», found in their…" canonical: "https://research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Transformers without Tears: Improving the…](https://md.research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/) / cited by # Who cites «Transformers without Tears: Improving the Normalization of Self-Attention» 73 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Transformers without Tears: Improving the Normalization of Self-Attention»](https://md.research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/) 1. **[Conformer: Convolution-augmented Transformer for Speech Recognition](https://md.research.elamur.ai/free/en/papers/gulati-2020-conformer-convolution-augmented-transformer-speech/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Anmol Gulati, James Qin, Chung-Cheng Chiu, et al.*2020 · 3,475 citations* 2. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations* 3. **[GPT-NeoX-20B: An Open-Source Autoregressive Language Model](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/) [BigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language Models](https://md.research.elamur.ai/free/en/venues/bigscience/)**Sidney Black, Stella Biderman, Eric Hallahan, et al.*2022 · 831 citations* 4. [**Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model arXiv:2201.11990**Shaden Smith, Mostofa Patwary, Brandon Norick, et al.*2022 · 615 citations*](https://md.research.elamur.ai/free/en/papers/smith-2022-using-deepspeed-megatron-train-megatron/) 5. **[Masked Language Model Scoring](https://md.research.elamur.ai/free/en/papers/salazar-2020-masked-language-model-scoring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Julian Salazar, Davis Liang, Toan Q. Nguyen, et al.*2020 · 447 citations* 6. [**FlauBERT: Unsupervised Language Model Pre-training for French arXiv:1912.05372**Hang Le, Loïc Vial, Jibril Frej, et al.*2019 · 299 citations*](https://md.research.elamur.ai/free/en/papers/le-2019-flaubert-unsupervised-language-model-pre/) 7. **[Understanding the Difficulty of Training Transformers](https://md.research.elamur.ai/free/en/papers/liu-2020-understanding-difficulty-training-transformers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyuan Liu, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 231 citations* 8. [**Transformer Quality in Linear Time arXiv:2202.10447**Weizhe Hua, Zihang Dai, Hanxiao Liu, et al.*2022 · 99 citations*](https://md.research.elamur.ai/free/en/papers/hua-2022-transformer-quality-linear-time/) 9. **[BERT Busters: Outlier Dimensions that Disrupt Transformers](https://md.research.elamur.ai/free/en/papers/kovaleva-2021-bert-busters-outlier-dimensions-that/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Olga Kovaleva, Saurabh Kulshreshtha, Anna Rogers, et al.*2021 · 90 citations* 10. [**Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents arXiv:2310.19923**Michael Gunther, Jackmin Ong, Isabelle Mohr, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/gunther-2023-jina-embeddings-2-8192-token/) 11. [**Distillation Scaling Laws arXiv:2502.08606**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/) 12. **[Joint Universal Syntactic and Semantic Parsing](https://md.research.elamur.ai/free/en/papers/eskin-2021-joint-universal-syntactic-semantic-parsing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Elias Stengel-Eskin, Kenton Murray, Sheng Zhang, et al.*2021 · 16 citations* 13. [**Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs arXiv:2504.07866**Yichun Yin, Wenyong Huang, Kaikai Song, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/yin-2025-pangu-ultra-pushing-limits/) 60 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/) — Transformers without Tears: Improving the Normalization of Self-Attention