Elamur Research⌕
☰
home / papers / RoBERTa: A Robustly Optimized BERT Pretraining… / cited by

Who cites «RoBERTa: A Robustly Optimized BERT Pretraining Approach»

9,837 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1293 with a page here, the most cited first · page 1 of 13 · 1–100 · ← back to «RoBERTa: A Robustly Optimized BERT Pretraining Approach»

1 2 … 10 … 13

  1. Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 14,178 citations
  2. Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerarXiv:1910.10683Colin Raffel, Noam Shazeer, Adam Roberts, et al.2019 · 11,325 citations
  3. Llama 2: Open Foundation and Fine-Tuned Chat ModelsarXiv:2307.09288Hugo Touvron, Louis Martin, Kevin Stone, et al.2023 · 9,669 citations
  4. LoRA: Low-Rank Adaptation of Large Language ModelsarXiv:2106.09685Edward J. Hu, Yelong Shen, Phillip Wallis, et al.2021 · 8,661 citations
  5. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  6. ChatGPT for Good? On Opportunities and Challenges of Large Language Models for EducationEnkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.2023 · 7,440 citations
  7. Longformer: The Long-Document TransformerarXiv:2004.05150Iz Beltagy, Matthew E. Peters, Arman Cohan2020 · 3,880 citations
  8. XLNet: Generalized Autoregressive Pretraining for Language UnderstandingarXiv:1906.08237Zhilin Yang, Zihang Dai, Yiming Yang, et al.2019 · 3,857 citations
  9. Measuring Massive Multitask Language UnderstandingarXiv:2009.03300Dan Hendrycks, Collin Burns, Steven Basart, et al.2020 · 3,620 citations
  10. Scaling Laws for Neural Language ModelsarXiv:2001.08361Jared Kaplan, Sam McCandlish, Tom Henighan, et al.2020 · 3,434 citations
  11. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  12. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  13. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  14. ALBERT: A Lite BERT for Self-supervised Learning of Language RepresentationsarXiv:1909.11942Zhenzhong Lan, Mingda Chen, Sebastian Goodman, et al.2019 · 2,806 citations
  15. Domain-Specific Language Model Pretraining for Biomedical Natural Language ProcessingarXiv:2007.15779Yu Gu; Robert Tinn; Hao Cheng; Michael Lucas; Naoto Usuyama; Xiaodong Liu; Tristan Naumann; Jianfeng Gao;, Hoifung Poon2020 · 2,674 citations
  16. Evaluating Large Language Models Trained on CodearXiv:2107.03374Mark Chen, Jerry Tworek, Heewoo Jun, et al.2021 · 2,659 citations
  17. UNITER: UNiversal Image-TExt Representation LearningLecture notes in computer scienceYen-Chun Chen, Linjie Li, Licheng Yu, et al.2019 · 2,418 citations
  18. DeBERTa: Decoding-enhanced BERT with Disentangled AttentionarXiv:2006.03654Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.2020 · 1,828 citations
  19. Pre-trained Models for Natural Language Processing: A SurveyarXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.2020 · 1,759 citations
  20. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
  21. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  22. BERTopic: Neural topic modeling with a class-based TF-IDF procedurearXiv:2203.05794Maarten Grootendorst2022 · 1,737 citations
  23. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  24. REALM: Retrieval-Augmented Language Model Pre-TrainingarXiv:2002.08909Kelvin Guu, Kenton Lee, Zora Tung, et al.2020 · 1,580 citations
  25. LEGAL-BERT: The Muppets straight out of Law SchoolFindings of the Association for Computational LinguisticsIlias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.2020 · 1,493 citations
  26. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
  27. LaMDA: Language Models for Dialog ApplicationsarXiv:2201.08239Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.2022 · 1,344 citations
  28. DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding SharingarXiv:2111.09543Pengcheng He, Jianfeng Gao, Weizhu Chen2021 · 1,320 citations
  29. AraBERT: Transformer-based Model for Arabic Language UnderstandingarXiv:2003.00104Wissam Antoun, Fady Baly, Hazem Hajj2020 · 1,304 citations
  30. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  31. CamemBERT: a Tasty French Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, et al.2019 · 1,269 citations
  32. What Makes Good In-Context Examples for GPT-3?Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning ArchitecturesJiachang Liu, Dinghan Shen, Yizhe Zhang, et al.2022 · 1,256 citations
  33. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
  34. VL-BERT: Pre-training of Generic Visual-Linguistic RepresentationsarXiv:1908.08530Weijie Su, Xizhou Zhu, Yue Cao, et al.2019 · 1,066 citations
  35. GPT Understands, TooAI OpenXiao Liu, Yanan Zheng, Zhengxiao Du, et al.2021 · 1,054 citations
  36. Big Bird: Transformers for Longer SequencesConference on Neural Information Processing Systems (NeurIPS)Manzil Zaheer, Guru Guruganesh, Avinava Dubey, et al.2020 · 1,023 citations
  37. GPQA: A Graduate-Level Google-Proof Q&A BenchmarkarXiv:2311.12022David Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023 · 1,018 citations
  38. AdapterFusion: Non-Destructive Task Composition for Transfer LearningarXiv:2005.00247 · Proceedings of EACL 2021Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al.2020 · 958 citations
  39. MPNet: Masked and Permuted Pre-training for Language UnderstandingarXiv:2004.09297Kaitao Song, Xu Tan, Tao Qin, et al.2020 · 957 citations
  40. TweetEval: Unified Benchmark and Comparative Evaluation for Tweet ClassificationarXiv:2010.12421Francesco Barbieri, Jose Camacho-Collados, Leonardo Neves, et al.2020 · 956 citations
  41. Extracting Training Data from Large Language ModelsarXiv:2012.07805Nicholas Carlini, Florian Tramer, Eric Wallace, et al.2020 · 955 citations
  42. Patient Knowledge Distillation for BERT Model CompressionarXiv:1908.09355Siqi Sun, Yu Cheng, Zhe Gan, et al.2019 · 947 citations
  43. LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingarXiv:1912.13318Yiheng Xu, Minghao Li, Lei Cui, et al.2019 · 896 citations
  44. Are NLP Models really able to Solve Simple Math Word Problems?Arkil Patel, Satwik Bhattamishra, Navin Goyal2021 · 890 citations
  45. TaPas: Weakly Supervised Table Parsing via Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.2020 · 847 citations
  46. Can Large Language Models Transform Computational Social Science?Computational LinguisticsCaleb Ziems, William Held, Omar Shaikh, et al.2023 · 790 citations
  47. Revisiting Pre-Trained Models for Chinese Natural Language ProcessingarXiv:2004.13922Yiming Cui, Wanxiang Che, Ting Liu, et al.2020 · 790 citations
  48. CORD-19: The COVID-19 Open Research DatasetWorkshop on NLP for COVID-19 at ACLLucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, et al.2020 · 695 citations
  49. Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text RetrievalarXiv:2007.00808Lee Xiong, Chenyan Xiong, Ye Li, et al.2020 · 688 citations

1 2 … 10 … 13

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/liu-2019-roberta-robustly-optimized-bert-pretraining/cited-by/