🧑‍🔬 Who cites Shwai He

66 citations of their works from 66 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · ← Shwai He

1. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
2. From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction TuningarXiv:2308.12032Ming Li, Yong Zhang, Zhitao Li, et al.2023 · 161 citations
3. PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language ModelsarXiv:2404.02948Fanxu Meng, Zhaohui Wang, Muhan Zhang2024 · 86 citations
4. Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and OpportunitiesarXiv:2408.07666Enneng Yang, Li Shen, Guibing Guo, et al.2024 · 79 citations
5. OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMsarXiv:2411.14199Akari Asai, Jacqueline He, Rulin Shao, et al.2024 · 62 citations
6. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language ModelsarXiv:2504.11468Hardy Chen, Haoqin Tu, Fali Wang, et al.2025 · 37 citations
7. What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Ming Li, Yanhong Li, Tianyi Zhou2025 · 15 citations
8. Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Chao Xue, Yao Wang, Mengqiao Liu, et al.2026 · 6 citations
9. Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode TheoryConference on Empirical Methods in Natural Language Processing (EMNLP)Ming Li, Nan Zhang, Chenrui Fan, et al.2025 · 6 citations
10. Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy ParadigmConference on Empirical Methods in Natural Language Processing (EMNLP)Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.2025 · 5 citations
11. ProFit: Leveraging High-Value Signals in SFT via Probability-Guided Token SelectionFindings of the Association for Computational LinguisticsTao Liu, Taiqiang Wu, Runming Yang, et al.2026 · 4 citations
12. Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT ReasoningFindings of the Association for Computational LinguisticsCehao Yang, Xueyuan Lin, Xiaojun Wu, et al.2026 · 4 citations
13. Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in RecommendationAnnual Meeting of the Association for Computational Linguistics (ACL)Tianjun Wei, Huizhong Guo, Yingpeng Du, et al.2026 · 1 citation
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
15. Calibrated Progressive Distillation: Co-Designing Curriculum and Target Mixing for Knowledge Distillation of Large Language ModelsFindings of the Association for Computational LinguisticsMengxiang Zhang, Lingyuan Liu2026
16. InstructDiff: Domain-Adaptive Data Selection via Contrastive Entropy for Efficient LLM Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Junyou Su, He Zhu, Xiao Luo, et al.2026
17. Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yitong Wang, Xue Han, WenChun Gao, et al.2026
18. SmolKalam: Ensemble Quality-Filtered Translation at Scale for High Quality Arabic Post-Training DataarXiv:2511.18411Sultan Alrashed, Chadi Helwe, Francesco Orabona2025

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