---
title: "Who cites Instruction Mining: Instruction — 72 citing papers"
description: "72 papers of the Elamur Research library cite «Instruction Mining: Instruction Data Selection for Tuning Large Language Models», found in their…"
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Instruction Mining: Instruction Data Selection…](https://md.research.elamur.ai/free/en/papers/cao-2023-instruction-mining-instruction-data-selection/) / cited by

# Who cites «Instruction Mining: Instruction Data Selection for Tuning Large Language Models»

72 papers of our library cite it (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · [← back to «Instruction Mining: Instruction Data Selection for Tuning Large Language Models»](https://md.research.elamur.ai/free/en/papers/cao-2023-instruction-mining-instruction-data-selection/)

1. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,974 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. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
4. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/)
5. [**LESS: Selecting Influential Data for Targeted Instruction Tuning arXiv:2402.04333**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 178 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/)
6. [**What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning arXiv:2312.15685**Wei Liu, Weihao Zeng, Keqing He, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-makes-good-data-alignment-comprehensive/)
7. **[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*
8. [**SaulLM-7B: A pioneering Large Language Model for Law arXiv:2403.03883**Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/colombo-2024-saullm-7b-pioneering-large-language/)
9. [**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/)
10. [**Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models arXiv:2310.02949**Xianjun Yang, Xiao Wang, Qi Zhang, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-shadow-alignment-ease-subverting-safely/)
11. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
12. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihan Dou, Enyu Zhou, Yan Liu, et al.*2024 · 93 citations*
13. [**DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving arXiv:2407.13690**Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-dart-math-difficulty-aware-rejection/)
14. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
15. **[One-Shot Learning as Instruction Data Prospector for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-one-shot-learning-as-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunshui Li, Binyuan Hui, Xiaobo Xia, et al.*2024 · 61 citations*
16. **[Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering](https://md.research.elamur.ai/free/en/papers/liu-2025-ontology-guided-reverse-thinking-makes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runxuan Liu, Bei Luo, Jiaqi Li, et al.*2025 · 15 citations*
17. **[Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 11 citations*
18. **[Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm](https://md.research.elamur.ai/free/en/papers/li-2025-add-one-incremental-sample-selection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.*2025 · 5 citations*
19. **[GATEAU: Selecting Influential Samples for Long Context Alignment](https://md.research.elamur.ai/free/en/papers/si-2025-gateau-selecting-influential-samples-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 5 citations*
20. [**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/)
21. **[ProFit: Leveraging High-Value Signals in SFT via Probability-Guided Token Selection](https://md.research.elamur.ai/free/en/papers/liu-2026-profit-leveraging-high-value-signals/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tao Liu, Taiqiang Wu, Runming Yang, et al.*2026 · 4 citations*
22. **[Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-select2reason-efficient-instruction-tuning-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cehao Yang, Xueyuan Lin, Xiaojun Wu, et al.*2026 · 4 citations*
23. **[Balancing Knowledge Breadth and Task Depth for Effective Domain Adaptation Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-balancing-knowledge-breadth-task-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mu Zhang, Yuxiang Chu, Guangya Yu, et al.*2026*
24. **[CypherSmith: Transforming Text-to-Cypher Generation for LLMs with Synthetic Data](https://md.research.elamur.ai/free/en/papers/zhang-2026-cyphersmith-transforming-text-cypher-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeyu Zhang, Kexuan Sun, Zheng Tang, et al.*2026*
25. **[Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-safeguarding-llm-fine-tuning-push/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haozhong Wang, Zhuo Li, Yibo Yang, et al.*2026*

47 more papers of our library cite it; they have no page here yet.

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