--- title: "Who cites Chengsong Huang — 102 papers of our library" description: "102 papers of the Elamur Research library cite the works of Chengsong Huang, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/chengsong-huang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/chengsong-huang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Chengsong Huang](https://md.research.elamur.ai/free/en/authors/chengsong-huang/) / cited by # Who cites Chengsong Huang 102 citations of their works from 102 papers of our library (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← Chengsong Huang](https://md.research.elamur.ai/free/en/authors/chengsong-huang/) 1. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/) 2. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/) 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. [**Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging arXiv:2310.11564**Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.*2023 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-personalized-soups-personalized-large-language/) 5. **[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* 6. [**Knowledge Fusion of Large Language Models arXiv:2401.10491**Fanqi Wan, Xinting Huang, Deng Cai, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wan-2024-knowledge-fusion-large-language-models/) 7. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/) 8. **[ReFT: Representation Finetuning for Language Models](https://md.research.elamur.ai/free/en/papers/wu-2024-reft-representation-finetuning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.*2024 · 74 citations* 9. [**AdaMerging: Adaptive Model Merging for Multi-Task Learning arXiv:2310.02575**Enneng Yang, Zhenyi Wang, Li Shen, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/) 10. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations* 11. **[Deep Model Fusion: A Survey](https://md.research.elamur.ai/free/en/papers/li-2023-deep-model-fusion-survey/) [IEEE Transactions on Neural Networks and Learning Systems](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-neural-networks-and-learning-systems/)**Weishi Li, Yong Peng, Miao Zhang, et al.*2023 · 49 citations* 12. **[Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts](https://md.research.elamur.ai/free/en/papers/tan-2024-personalized-pieces-efficient-personalized-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoxuan Tan, Zheyuan Liu, Meng Jiang*2024 · 40 citations* 13. [**StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements**Jillian Fisher, Skyler Hallinan, Ximing Lu, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/fisher-2024-styleremix-interpretable-authorship-obfuscation-distillation/) 14. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations* 15. **[Nature-Inspired Population-Based Evolution of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-nature-inspired-population-based-evolution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Peng Ye, Xiaocui Yang, et al.*2026 · 8 citations* 16. **[LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint](https://md.research.elamur.ai/free/en/papers/ma-2025-led-merging-mitigating-safety-utility/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Ma, Dongrui Liu, Qian Chen, et al.*2025 · 5 citations* 17. **[K-Merge: Online Continual Merging of Adapters for On-device Large Language Models](https://md.research.elamur.ai/free/en/papers/shenaj-2026-k-merge-online-continual-merging/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donald Shenaj, Ondrej Bohdal, Taha Ceritli, et al.*2026 · 2 citations* 18. **[Why Do More Experts Fail? A Theoretical Analysis of Model Merging](https://md.research.elamur.ai/free/en/papers/wang-2026-why-do-more-experts-fail/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijing Wang, Xingle Xu, YongKang Liu, et al.*2026 · 2 citations* 19. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation* 20. [**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/) 21. **[SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMs](https://md.research.elamur.ai/free/en/papers/shaaban-2026-securegate-learning-when-reveal-pii/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohamed Shaaban, Mohamed Elmahallawy*2026* 81 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/chengsong-huang/) — Chengsong Huang