---
title: "Who cites Zhiyuan Zhang — 315 papers of our library"
description: "315 papers of the Elamur Research library cite the works of Zhiyuan Zhang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/zhiyuan-zhang/cited-by/"
---
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# Who cites Zhiyuan Zhang

315 citations of their works from 315 papers of our library (of the 141,840 whose bibliographies we read) · 17 with a page here, the most cited first · [← Zhiyuan Zhang](https://md.research.elamur.ai/free/en/authors/zhiyuan-zhang/)

1. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 710 citations*
2. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 422 citations*
3. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
4. [**RRHF: Rank Responses to Align Language Models with Human Feedback without tears arXiv:2304.05302**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/)
5. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
6. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 187 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
7. **[How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*
8. **[Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models](https://md.research.elamur.ai/free/en/papers/shao-2024-assisting-writing-wikipedia-like-articles/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yijia Shao, Yucheng Jiang, Theodore Kanell, et al.*2024 · 126 citations*
9. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
10. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
11. **[RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models](https://md.research.elamur.ai/free/en/papers/yang-2021-rap-robustness-aware-perturbations-defending/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenkai Yang, Yankai Lin, Peng Li, et al.*2021 · 112 citations*
12. **[Data Interpreter: An LLM Agent for Data Science](https://md.research.elamur.ai/free/en/papers/hong-2025-data-interpreter-llm-agent-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sirui Hong, Yizhang Lin, Bang Liu, et al.*2025 · 89 citations*
13. [**SemEval-2022 Task 3: PreTENS — Evaluating Neural Networks on Presuppositional Semantic Knowledge**Roberto Zamparelli, Shammur Chowdhury, Dominique Brunato, et al.*2022 · 8 citations*](https://md.research.elamur.ai/free/en/papers/zamparelli-2022-semeval-2022-task-3-pretens/)
14. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
15. **[Integrating TEI, NER/NEL, Textometry, and Linked Data for a Semantically Enriched Interview Corpus](https://md.research.elamur.ai/free/en/papers/stankovic-2026-integrating-tei-ner-nel-textometry/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ranka Stankovic, Tamara Vučenović, Biljana Rujević, et al.*2026*
16. **[LLM-as-a-Jury for Machine Translation Publishability Assessment](https://md.research.elamur.ai/free/en/papers/yanishevsky-2026-llm-as-jury-machine-translation/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Alex Yanishevsky, Olivia Norris*2026*
17. **[To Write or to Automate Linguistic Prompts, That Is the Question](https://md.research.elamur.ai/free/en/papers/torron-2026-write-or-automate-linguistic-prompts/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Marina Sánchez-Torrón, Daria Akselrod, Jason Rauchwerk*2026*

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

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