🧑‍🔬 Who cites Xingjian Shi

150 citations of their works from 148 papers of our library (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · ← Xingjian Shi

1. Context-Aware Attentive Knowledge TracingACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD)Aritra Ghosh, Neil Heffernan, Andrew S. Lan2020 · 601 citations
2. Knowledge Tracing: A SurveyACM Computing SurveysGhodai Abdelrahman, Qing Wang, Bernardo Nunes2023 · 480 citations
3. LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.2023 · 401 citations
4. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
5. A self-attentive model for knowledge tracingPandey2019 · 213 citations
6. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
7. Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather ForecastarXiv:2211.02556Kaifeng Bi, Lingxi Xie, Hengheng Zhang, et al.2022 · 133 citations
8. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
9. Unlearn What You Want to Forget: Efficient Unlearning for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaao Chen, Diyi Yang2023 · 124 citations
10. Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction TuningarXiv:2309.05444Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.2023 · 69 citations
11. AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-TuningTransactions of the Association for Computational Linguistics (TACL)Han Zhou, Xingchen Wan, Ivan Vulić, et al.2024 · 46 citations
12. Fine-tuning Large Language Models with Limited Data: A Survey and Practical GuideTransactions of the Association for Computational Linguistics (TACL)Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.2026 · 7 citations
13. CUFE at StanceEval2024: Arabic Stance Detection with Fine-Tuned Llama-3 ModelArabic Natural Language Processing Conference (ArabicNLP)Michael Ibrahim2024 · 4 citations
14. CUFE at NADI 2024 shared task: Fine-Tuning Llama-3 To Translate From Arabic Dialects To Modern Standard ArabicArabic Natural Language Processing Conference (ArabicNLP)Michael Ibrahim2024 · 2 citations
15. LLM-KT: Enhancing Large Language Models with Knowledge Tracing via Multi-Level Plug-and-Play AlignmentFindings of the Association for Computational LinguisticsZiwei Wang, Jie Zhou, Qin Chen, et al.2026 · 1 citation
16. 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
17. Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)YongKang Liu, Xingle Xu, Ercong Nie, et al.2026
18. Tracing Mathematical Proficiency Through Problem-Solving ProcessesFindings of the Association for Computational LinguisticsJungyang Park, Suho Kang, Jaewoo Park, et al.2026
19. Review and Performance Comparison of Deep Knowledge Tracing Models (深度知识追踪模型综述和性能比较)Journal of SoftwareYu Wang (王宇), Mengxia Zhu (朱梦霞), Shanghui Yang (杨尚辉), et al.2022

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