🧑‍🔬 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

1. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
2. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
3. Efficient Large Language Models: A SurveyarXiv:2312.03863Zhongwei Wan, Xin Wang, Che Liu, et al.2023 · 110 citations
4. Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter MergingarXiv:2310.11564Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.2023 · 102 citations
5. LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style PluginAnnual Meeting of the Association for Computational Linguistics (ACL)Shihan Dou, Enyu Zhou, Yan Liu, et al.2024 · 93 citations
6. Knowledge Fusion of Large Language ModelsarXiv:2401.10491Fanqi Wan, Xinting Huang, Deng Cai, et al.2024 · 82 citations
7. Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and OpportunitiesarXiv:2408.07666Enneng Yang, Li Shen, Guibing Guo, et al.2024 · 79 citations
8. ReFT: Representation Finetuning for Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.2024 · 74 citations
9. AdaMerging: Adaptive Model Merging for Multi-Task LearningarXiv:2310.02575Enneng Yang, Zhenyi Wang, Li Shen, et al.2023 · 59 citations
10. The Art of Saying No: Contextual Noncompliance in Language ModelsConference on Neural Information Processing Systems (NeurIPS)Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.2024 · 56 citations
11. Deep Model Fusion: A SurveyIEEE Transactions on Neural Networks and Learning SystemsWeishi Li, Yong Peng, Miao Zhang, et al.2023 · 49 citations
12. Personalized Pieces: Efficient Personalized Large Language Models through Collaborative EffortsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhaoxuan Tan, Zheyuan Liu, Meng Jiang2024 · 40 citations
13. StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style ElementsJillian Fisher, Skyler Hallinan, Ximing Lu, et al.2024 · 16 citations
14. When One LLM Drools, Multi-LLM Collaboration RulesAnnual Meeting of the Association for Computational Linguistics (ACL)Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.2026 · 14 citations
15. Nature-Inspired Population-Based Evolution of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (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-DisjointAnnual Meeting of the Association for Computational Linguistics (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 ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Donald Shenaj, Ondrej Bohdal, Taha Ceritli, et al.2026 · 2 citations
18. Why Do More Experts Fail? A Theoretical Analysis of Model MergingAnnual Meeting of the Association for Computational Linguistics (ACL)Zijing Wang, Xingle Xu, YongKang Liu, et al.2026 · 2 citations
19. Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration SystemsAnnual Meeting of the Association for Computational Linguistics (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
21. SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Mohamed Shaaban, Mohamed Elmahallawy2026

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

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