---
title: "Who cites Junyuan Shang — 222 papers of our library"
description: "222 papers of the Elamur Research library cite the works of Junyuan Shang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/junyuan-shang/cited-by/"
---
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# Who cites Junyuan Shang

237 citations of their works from 222 papers of our library (of the 149,439 whose bibliographies we read) · 49 with a page here, the most cited first · [← Junyuan Shang](https://md.research.elamur.ai/free/en/authors/junyuan-shang/)

1. **[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*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
3. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,556 citations*
4. **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,551 citations*
5. **[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*
6. **[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*
7. [**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/)
8. [**Ethical and social risks of harm from Language Models arXiv:2112.04359**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 456 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
9. [**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/)
10. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
11. **[xLSTM: Extended Long Short-Term Memory](https://md.research.elamur.ai/free/en/papers/beck-2024-xlstm-extended-long-short-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.*2024 · 296 citations*
12. **[Predictability and Surprise in Large Generative Models](https://md.research.elamur.ai/free/en/papers/ganguli-2022-predictability-surprise-large-generative-models/) [ACM Conference on Fairness, Accountability, and Transparency (FAccT)](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/)**Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.*2022 · 268 citations*
13. **[A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Xiaowei Huang, Wenjie Ruan, Wei Huang, et al.*2023 · 199 citations*
14. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
15. **[MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models](https://md.research.elamur.ai/free/en/papers/wen-2024-mindmap-knowledge-graph-prompting-sparks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilin Wen, Zifeng Wang, Jimeng Sun*2024 · 158 citations*
16. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
17. **[Humans or LLMs as the Judge? A Study on Judgement Bias](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-or-llms-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 133 citations*
18. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
19. **[Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-not-all-countries-celebrate-thanksgiving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Wang, Wenxiang Jiao, Jingyuan Huang, et al.*2024 · 96 citations*
20. [**Humans or LLMs as the Judge? A Study on Judgement Biases arXiv:2402.10669**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-llms-judge-study-judgement/)
21. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
22. [**When More is Less: Understanding Chain-of-Thought Length in LLMs arXiv:2502.07266**Yuyang Wu, Yifei Wang, Ziyu Ye, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-more-less-understanding-chain-thought/)
23. [**CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility arXiv:2307.09705**Guohai Xu, Jiayi Liu, Ming Yan, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-cvalues-measuring-values-chinese/)
24. [**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/)
25. [**Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models arXiv:2308.11764**Mohamed Elaraby, Mengyin Lu, Jacob Dunn, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/elaraby-2023-halo-estimation-reduction-hallucinations-open/)
26. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
27. [**PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing arXiv:2303.10845**Xiaozhe Ren, Pingyi Zhou, Xinfan Meng, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ren-2023-pangu-sigma-trillion-parameter/)
28. [**M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models arXiv:2305.10263**Chuang Liu, Renren Jin, Yuqi Ren, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-m3ke-massive-multi-level/)
29. **[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*
30. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
31. **[AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-aramus-pushing-limits-data-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaad Alghamdi, Xinyu Duan, Wei Jiang, et al.*2023 · 21 citations*
32. **[Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains](https://md.research.elamur.ai/free/en/papers/tan-2025-think-silently-think-fast-dynamic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenhui Tan, Jiaze Li, Jianzhong Ju, et al.*2025 · 19 citations*
33. [**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/)
34. **[Beyond Dialogue: A Profile-Dialogue Alignment Framework Towards General Role-Playing Language Model](https://md.research.elamur.ai/free/en/papers/yu-2025-beyond-dialogue-profile-dialogue-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yeyong Yu, Runsheng Yu, Haojie Wei, et al.*2025 · 10 citations*
35. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
36. **[Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key Information](https://md.research.elamur.ai/free/en/papers/chen-2025-improving-reasoning-capabilities-small-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yao Chen, Jiawei Sheng, Wenyuan Zhang, et al.*2025 · 10 citations*
37. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
38. [**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/)
39. [**Baichuan Alignment Technical Report arXiv:2410.14940**Mingan Lin, Fan Yang, Yanjun Shen, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-baichuan-alignment-technical-report/)
40. **[SpiralThinker: Latent Reasoning through an Iterative Process with Text–Latent Interleaving](https://md.research.elamur.ai/free/en/papers/piao-2026-spiralthinker-latent-reasoning-through-iterative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shengmin Piao, Sanghyun Park*2026 · 1 citation*
41. **[CARE-CR: Context-Aware Routing and Expert Fusion for Multi-Preference Cognitive Restructuring](https://md.research.elamur.ai/free/en/papers/qi-2026-care-cr-context-aware-routing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongzhi Qi, Liangcheng Wang, Yijing YU, et al.*2026*
42. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/zhao-2026-comet-collaborative-memory-transformer-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runsong Zhao, Shilei Liu, Jiwei Tang, et al.*2026*
43. **[DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition](https://md.research.elamur.ai/free/en/papers/zhang-2026-duivrs-2-llm-based-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Le Zhang, Shengming Zhang, Rui Zha, et al.*2026*
44. **[LoopCoder: Scaling Code Intelligence via Looped Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-loopcoder-scaling-code-intelligence-looped/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Yang, Wei Zhang, Shuyue Guo, et al.*2026*
45. **[MedCPI: A Construct–Personalize–Integrate Framework for KG-enhanced Clinical Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-medcpi-construct-personalize-integrate-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hang Wang, Hang Dong, Lu Liu*2026*
46. **[Parallel Test-Time Scaling for Latent Reasoning Models](https://md.research.elamur.ai/free/en/papers/you-2026-parallel-test-time-scaling-latent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runyang You, Yongqi Li, Meng Liu, et al.*2026*
47. [**From Foundation Intelligence to General Intelligence: Status and Prospects of Large-Model-Based GenAI and AGI (从基础智能到通用智能: 基于大模型的GenAI和AGI之现状与展望) Acta Automatica Sinica (自动化学报)**Qinghai Miao (缪青海), Xingxia Wang (王兴霞), Jing Yang (杨静), et al.*2024*](https://md.research.elamur.ai/free/en/papers/miao-2024-foundation-intelligence-general/)
48. [**Questions After ChatGPT: Opportunities and Challenges of Very Large Pre-trained Models (问答ChatGPT之后: 超大预训练模型的机遇和挑战) Acta Automatica Sinica (自动化学报)**Jingwei Lu (卢经纬), Chao Guo (郭超), Xingyuan Dai (戴星原), et al.*2023*](https://md.research.elamur.ai/free/en/papers/lu-2023-questions-after-chatgpt/)
49. **[Survey on Commonsense Question Answering (常识问答研究综述)](https://md.research.elamur.ai/free/en/papers/fan-2023-commonsense-question-answering/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yifan Fan (范怡帆), Bowei Zou (邹博伟), Qingting Xu (徐庆婷), et al.*2023*

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

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