🧑‍🔬 Who cites Hrant Khachatrian

117 citations of their works from 117 papers of our library (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · ← Hrant Khachatrian

1. LoRA: Low-Rank Adaptation of Large Language ModelsarXiv:2106.09685Edward J. Hu, Yelong Shen, Phillip Wallis, et al.2021 · 8,661 citations
2. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language ProcessingACM Computing SurveysPengfei Liu, Weizhe Yuan, Jinlan Fu, et al.2021 · 5,423 citations
3. The Power of Scale for Parameter-Efficient Prompt TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Brian Lester, Rami Al-Rfou, Noah Constant2021 · 4,287 citations
4. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
5. Pre-trained Models for Natural Language Processing: A SurveyarXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.2020 · 1,759 citations
6. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,556 citations
7. PPT: Pre-trained Prompt Tuning for Few-shot LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxian Gu, Xu Han, Zhiyuan Liu, et al.2022 · 471 citations
8. Automatic Prompt Optimization with “Gradient Descent” and Beam SearchConference on Empirical Methods in Natural Language Processing (EMNLP)Reid Pryzant, Dan Iter, Jerry Li, et al.2023 · 409 citations
9. Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Shengding Hu, Ning Ding, Huadong Wang, et al.2022 · 362 citations
10. RLPrompt: Optimizing Discrete Text Prompts with Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.2022 · 338 citations
11. CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal DependenciesDaniel Zeman, Jan Hajič, Martin Popel, et al.2018 · 317 citations
12. SPoT: Better Frozen Model Adaptation through Soft Prompt TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Tu Vu, Brian Lester, Noah Constant, et al.2022 · 306 citations
13. Surface Form Competition: Why the Highest Probability Answer Isn't Always RightConference on Empirical Methods in Natural Language Processing (EMNLP)Ari Holtzman, Peter West, Vered Shwartz, et al.2021 · 277 citations
14. Dynamic Prefix-Tuning for Generative Template-based Event ExtractionAnnual Meeting of the Association for Computational Linguistics (ACL)Xiao Liu, Heyan Huang, Ge Shi, et al.2022 · 145 citations
15. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
16. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
17. CPM-2: Large-scale Cost-effective Pre-trained Language ModelsAI OpenZhengyan Zhang, Yuxian Gu, Xu Han, et al.2021 · 102 citations
18. True Few-Shot Learning with Prompts–-A Real-World PerspectiveTransactions of the Association for Computational Linguistics (TACL)Timo Schick, Hinrich Schütze2022 · 96 citations
19. PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language ModelsarXiv:2404.02948Fanxu Meng, Zhaohui Wang, Muhan Zhang2024 · 86 citations
20. Fairness-guided Few-shot Prompting for Large Language ModelsarXiv:2303.13217Huan Ma, Changqing Zhang, Yatao Bian, et al.2023 · 64 citations
21. The Life Cycle of Knowledge in Big Language Models: A SurveyarXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024Boxi Cao, Hongyu Lin, Xianpei Han, et al.2023 · 31 citations
22. Infusing Hierarchical Guidance into Prompt Tuning: A Parameter-Efficient Framework for Multi-level Implicit Discourse Relation RecognitionAnnual Meeting of the Association for Computational Linguistics (ACL)Haodong Zhao, Ruifang He, Mengnan Xiao, et al.2023 · 19 citations
23. Topic-Guided Sampling For Data-Efficient Multi-Domain Stance DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Erik Arakelyan, Arnav Arora, Isabelle Augenstein2023 · 19 citations
24. UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter Efficient Fine-Tuning of Large ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xueyan Zhang, Jinman Zhao, Zhifei Yang, et al.2025 · 14 citations
25. Enhancing Lexical Relation Mining with Structured Sememe KnowledgeAnnual Meeting of the Association for Computational Linguistics (ACL)Hansi Wang, Qiliang Liang, Yue Wang, et al.2026

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