---
title: "Who cites Xin Tian — 267 papers of our library"
description: "267 papers of the Elamur Research library cite the works of Xin Tian, found in their bibliographies; the most cited first."
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---
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# Who cites Xin Tian

271 citations of their works from 267 papers of our library (of the 149,439 whose bibliographies we read) · 58 with a page here, the most cited first · [← Xin Tian](https://md.research.elamur.ai/free/en/authors/xin-tian/)

1. [**RoBERTa: A Robustly Optimized BERT Pretraining Approach arXiv:1907.11692**Yinhan Liu, Myle Ott, Naman Goyal, et al.*2019 · 9,837 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-roberta-robustly-optimized-bert-pretraining/)
2. **[Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,423 citations*
3. **[SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,616 citations*
4. [**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/)
5. [**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/)
6. **[Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) [IEEE/ACM Transactions on Audio Speech and Language Processing](https://md.research.elamur.ai/free/en/venues/ieee-acm-transactions-on-audio-speech-and-language-processing/)**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,490 citations*
7. **[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*
8. **[K-BERT: Enabling Language Representation with Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,019 citations*
9. **[ERNIE 2.0: A Continual Pre-training Framework for Language Understanding](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-2-0-continual/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 995 citations*
10. [**Revisiting Pre-Trained Models for Chinese Natural Language Processing arXiv:2004.13922**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2020 · 790 citations*](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/)
11. [**GLM-130B: An Open Bilingual Pre-trained Model arXiv:2210.02414**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 786 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/)
12. **[TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 692 citations*
13. **[A Robustly Optimized BERT Pre-training Approach with Post-training](https://md.research.elamur.ai/free/en/papers/zhuang-2021-robustly-optimized-bert-pre-training/) [Chinese National Conference on Computational Linguistics](https://md.research.elamur.ai/free/en/venues/ccl/)**Liu Zhuang, Lin Wayne, Shi Ya, et al.*2021 · 587 citations*
14. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework arXiv:2202.03052**Peng Wang, An Yang, Rui Men, et al.*2022 · 467 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
15. **[FastBERT: a Self-distilling BERT with Adaptive Inference Time](https://md.research.elamur.ai/free/en/papers/liu-2020-fastbert-self-distilling-bert-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weijie Liu, Peng Zhou, Zhiruo Wang, et al.*2020 · 383 citations*
16. **[Synthetic QA Corpora Generation with Roundtrip Consistency](https://md.research.elamur.ai/free/en/papers/alberti-2019-synthetic-qa-corpora-generation-roundtrip/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chris Alberti, Daniel Andor, Emily Pitler, et al.*2019 · 361 citations*
17. **[SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/tian-2020-skep-sentiment-knowledge-enhanced-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Tian, Can Gao, Xinyan Xiao, et al.*2020 · 333 citations*
18. [**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 · 332 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
19. [**CLUE: A Chinese Language Understanding Evaluation Benchmark arXiv:2004.05986**Liang Xu, Hai Hu, Xuanwei Zhang, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/)
20. **[Packed Levitated Marker for Entity and Relation Extraction](https://md.research.elamur.ai/free/en/papers/ye-2022-packed-levitated-marker-entity-relation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deming Ye, Yankai Lin, Peng Li, et al.*2022 · 189 citations*
21. **[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/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Dongling Xiao, Han Zhang, Yukun Li, et al.*2020 · 163 citations*
22. [**PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation arXiv:2104.12369**Wei Zeng, Xiaozhe Ren, Teng Su, et al.*2021 · 161 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2021-pangu-alpha-large-scale/)
23. [**A Review on Language Models as Knowledge Bases arXiv:2204.06031**Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.*2022 · 150 citations*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2022-review-language-models-knowledge-bases/)
24. **[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2020-cpm-large-scale-generative/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Zhengyan Zhang, Xu Han, Hao Zhou, et al.*2020 · 150 citations*
25. **[RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder](https://md.research.elamur.ai/free/en/papers/xiao-2022-retromae-pre-training-retrieval-oriented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shitao Xiao, Zheng Liu, Yingxia Shao, et al.*2022 · 145 citations*
26. **[ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/qin-2021-erica-improving-entity-relation-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujia Qin, Yankai Lin, Ryuichi Takanobu, et al.*2021 · 139 citations*
27. [**When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset arXiv:2104.08671**Lucia Zheng, Neel Guha, Brandon R. Anderson, et al.*2021 · 134 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-pretraining-help-assessing-self-supervised/)
28. **[Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Dong Yu, et al.*2019 · 133 citations*
29. **[Knowledge Enhanced Masked Language Model for Stance Detection](https://md.research.elamur.ai/free/en/papers/kawintiranon-2021-knowledge-enhanced-masked-language-model/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kornraphop Kawintiranon, Lisa Singh*2021 · 119 citations*
30. **[True Few-Shot Learning with Prompts–-A Real-World Perspective](https://md.research.elamur.ai/free/en/papers/schick-2022-true-few-shot-learning-prompts/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Timo Schick, Hinrich Schütze*2022 · 96 citations*
31. **[POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection](https://md.research.elamur.ai/free/en/papers/liu-2022-politics-pretraining-same-story-article/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yujian Liu, Xinliang Frederick Zhang, David Wegsman, et al.*2022 · 70 citations*
32. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/)
33. [**FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark arXiv:2107.07498**Liang Xu, Xiaojing Lu, Chenyang Yuan, et al.*2021 · 54 citations*](https://md.research.elamur.ai/free/en/papers/xu-2021-fewclue-chinese-few-shot/)
34. [**Parameter-Efficient Fine-Tuning Design Spaces arXiv:2301.01821**Jiaao Chen, Aston Zhang, Xingjian Shi, et al.*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/)
35. **[Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English](https://md.research.elamur.ai/free/en/papers/li-2021-exploring-text-transformers-aaai-2021/) [Communications in computer and information science](https://md.research.elamur.ai/free/en/venues/communications-in-computer-and-information-science/)**Xiangyang Li, Yu Xia, Xiang Long, et al.*2021 · 44 citations*
36. **[SLING: Sino Linguistic Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2022-sling-sino-linguistic-evaluation-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yixiao Song, Kalpesh Krishna, Rajesh Bhatt, et al.*2022 · 41 citations*
37. [**ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding arXiv:2210.06155**Qiming Peng, Yinxu Pan, Wenjin Wang, et al.*2022 · 40 citations*](https://md.research.elamur.ai/free/en/papers/peng-2022-ernie-layout-layout-knowledge/)
38. **[Neural Sarcasm Detection using Conversation Context](https://md.research.elamur.ai/free/en/papers/jaiswal-2020-neural-sarcasm-detection-conversation-context/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Nikhil Jaiswal*2020 · 32 citations*
39. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
40. **[Sub-Character Tokenization for Chinese Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/si-2023-sub-character-tokenization-chinese-pretrained/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chenglei Si, Zhengyan Zhang, Yingfa Chen, et al.*2023 · 29 citations*
41. **[DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine](https://md.research.elamur.ai/free/en/papers/qiu-2022-dureader-retrieval-large-scale/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yifu Qiu, Hongyu Li, Yingqi Qu, et al.*2022 · 27 citations*
42. **[Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 27 citations*
43. [**ERNIE-Doc: A Retrospective Long-Document Modeling Transformer arXiv:2012.15688**Siyu Ding, Junyuan Shang, Shuohuan Wang, et al.*2020 · 27 citations*](https://md.research.elamur.ai/free/en/papers/ding-2020-ernie-doc-retrospective-long/)
44. [**TeleChat Technical Report arXiv:2401.03804**Zhongjiang He, Zihan Wang, Xinzhang Liu, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-telechat-technical-report/)
45. [**ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding arXiv:2010.12148**Dongling Xiao, Yu-Kun Li, Han Zhang, et al.*2020 · 22 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gram-pre-training/)
46. **[ConnPrompt: Connective-cloze Prompt Learning for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/xiang-2022-connprompt-connective-cloze-prompt-learning/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Wei Xiang, Zhenglin Wang, Lu Dai, et al.*2022 · 21 citations*
47. **[TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks](https://md.research.elamur.ai/free/en/papers/long-2020-ted-cdb-large-scale-chinese/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wanqiu Long, Bonnie Webber, Deyi Xiong*2020 · 21 citations*
48. [**JABER and SABER: Junior and Senior Arabic BERt arXiv:2112.04329**Abbas Ghaddar, Yimeng Wu, Ahmad Rashid, et al.*2021 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2021-jaber-saber-junior-senior-arabic/)
49. **[X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/han-2022-x-pudu-semeval-2022-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Yaqian Han, Yekun Chai, Shuohuan Wang, et al.*2022 · 15 citations*
50. [**DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World Applications arXiv:2004.11142**Hongxuan Tang, Hongyu Li, Jing Liu, et al.*2020 · 13 citations*](https://md.research.elamur.ai/free/en/papers/tang-2020-dureader-robust-chinese-dataset/)
51. [**CLEVA: Chinese Language Models EVAluation Platform arXiv:2308.04813**Yanyang Li, Jianqiao Zhao, Duo Zheng, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cleva-chinese-language-models/)
52. [**PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation arXiv:2312.17276**Yunhe Wang, Hanting Chen, Yehui Tang, et al.*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pangu-pi-enhancing-language/)
53. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding arXiv:2205.10687**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/)
54. [**PanGu-π Pro:Rethinking Optimization and Architecture for Tiny Language Models arXiv:2402.02791**Yehui Tang, Kai Han, Fangcheng Liu, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-pangu-pi-pro-rethinking/)
55. **[Unveiling the Deficiencies of Pre-trained Text-and-Layout Models in Real-world Visually-rich Document Information Extraction](https://md.research.elamur.ai/free/en/papers/zhang-2026-unveiling-deficiencies-pre-trained-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chong Zhang, Yixi Zhao, Yulu Xie, et al.*2026 · 1 citation*
56. [**Aquila2 Technical Report arXiv:2408.07410**Bo-Wen Zhang, Liangdong Wang, Jijie Li, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aquila2-technical-report/)
57. **[Beyond Ranking: Fine-Grained Diagnostics and Self-Improvement for MLLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-beyond-ranking-fine-grained-diagnostics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingze Xu, Zijing Zhao, Qiming Peng, et al.*2026*
58. **[Morphology-Aware Multi-Granularity Representation Learning for Agglutinative Languages](https://md.research.elamur.ai/free/en/papers/zhang-2026-morphology-aware-multi-granularity-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghao Zhang, Na Liu, Jiajia Ma, et al.*2026*

209 more citing papers of our library have no page here yet.

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