---
title: "Who cites Lion: Adversarial Distillation of — 36 citing papers"
description: "36 papers of the Elamur Research library cite «Lion: Adversarial Distillation of Proprietary Large Language Models», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/jiang-2023-lion-adversarial-distillation-proprietary-large/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Lion: Adversarial Distillation of Proprietary…](https://md.research.elamur.ai/free/en/papers/jiang-2023-lion-adversarial-distillation-proprietary-large/) / cited by

# Who cites «Lion: Adversarial Distillation of Proprietary Large Language Models»

36 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «Lion: Adversarial Distillation of Proprietary Large Language Models»](https://md.research.elamur.ai/free/en/papers/jiang-2023-lion-adversarial-distillation-proprietary-large/)

1. **[A Survey on Model Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations*
2. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
3. [**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/)
4. **[FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-followbench-multi-level-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.*2024 · 86 citations*
5. **[Learning to Edit: Aligning LLMs with Knowledge Editing](https://md.research.elamur.ai/free/en/papers/jiang-2024-learning-edit-aligning-llms-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Chuhan Wu, et al.*2024 · 39 citations*
6. **[DDK: Distilling Domain Knowledge for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-ddk-distilling-domain-knowledge-efficient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.*2024 · 23 citations*
7. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
8. **[Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs](https://md.research.elamur.ai/free/en/papers/anshumann-2025-sparse-logit-sampling-accelerating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anshumann, Mohd Abbas Zaidi, Akhil Kedia, et al.*2025 · 6 citations*
9. **[ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation Attacks](https://md.research.elamur.ai/free/en/papers/lv-2026-reasmark-robust-watermark-attributing-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peizhuo Lv, Ruihua Zhou, Yunpeng Li, et al.*2026*
10. **[Teaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies](https://md.research.elamur.ai/free/en/papers/ye-2026-teaching-language-models-check-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Ye, Raul Santos-Rodriguez, Edwin Simpson*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/jiang-2023-lion-adversarial-distillation-proprietary-large/) — Lion: Adversarial Distillation of Proprietary Large Language Models