🔗 Who cites «Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks»

632 papers of our library cite it (of the 149,439 whose bibliographies we read) · 57 with a page here, the most cited first · ← back to «Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks»

1. Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 14,178 citations
2. Learning Transferable Architectures for Scalable Image RecognitionIEEE Computer Society Conference on Computer Vision and Pattern RecognitionBarret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.2017 · 6,583 citations
3. 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
4. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
5. Relational inductive biases, deep learning, and graph networksarXiv:1806.01261Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.2018 · 2,335 citations
6. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
7. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
8. Memory Aware Synapses: Learning what (not) to forgetLecture notes in computer scienceRahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, et al.2017 · 1,608 citations
9. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
10. MetaGPT: Meta Programming for A Multi-Agent Collaborative FrameworkarXiv:2308.00352Sirui Hong, Mingchen Zhuge, Jiaqi Chen, et al.2023 · 630 citations
11. Transferable Multi-Domain State Generator for Task-Oriented Dialogue SystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl, et al.2019 · 628 citations
12. Massively Multilingual Neural Machine Translation in the Wild: Findings and ChallengesarXiv:1907.05019Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.2019 · 564 citations
13. The Natural Language Decathlon: Multitask Learning as Question AnsweringarXiv:1806.08730Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, et al.2018 · 545 citations
14. Meta-Learning for Low-Resource Neural Machine TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Jiatao Gu, Yong Wang, Yun Chen, et al.2018 · 456 citations
15. Weight Poisoning Attacks on Pretrained ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Keita Kurita, Paul Michel, Graham Neubig2020 · 416 citations
16. True Few-Shot Learning with Language ModelsarXiv:2105.11447Ethan Perez, Douwe Kiela, Kyunghyun Cho2021 · 412 citations
17. A Survey on Recent Approaches for Natural Language Processing in Low-Resource ScenariosConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Michael A. Hedderich, Lukas Lange, Heike Adel, et al.2021 · 401 citations
18. A Survey on Model Compression for Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Xunyu Zhu, Jian Li, Yong Liu, et al.2024 · 381 citations
19. Universal Neural Machine Translation for Extremely Low Resource LanguagesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jiatao Gu, Hany Hassan, Jacob Devlin, et al.2018 · 361 citations
20. Few-NERD: A Few-shot Named Entity Recognition DatasetAnnual Meeting of the Association for Computational Linguistics (ACL)Ning Ding, Guangwei Xu, Yulin Chen, et al.2021 · 336 citations
21. AugGPT: Leveraging ChatGPT for Text Data AugmentationIEEE Transactions on Big DataHaixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li2023 · 306 citations
22. Diverse Few-Shot Text Classification with Multiple MetricsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Mo Yu, Xiaoxiao Guo, Jinfeng Yi, et al.2018 · 291 citations
23. Induction Networks for Few-Shot Text ClassificationConference on Empirical Methods in Natural Language Processing (EMNLP)Ruiying Geng, Binhua Li, Yongbin Li, et al.2019 · 263 citations
24. Survey of Low-Resource Machine TranslationComputational LinguisticsBarry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.2022 · 251 citations
25. Learning and Evaluating General Linguistic IntelligencearXiv:1901.11373Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor, et al.2019 · 248 citations
26. Transformers learn in-context by gradient descentarXiv:2212.07677Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.2022 · 247 citations
27. Personalizing Dialogue Agents via Meta-LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Andrea Madotto, Zhaojiang Lin, Chien-Sheng Wu, et al.2019 · 246 citations
28. Noisy Channel Language Model Prompting for Few-Shot Text ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Sewon Min, Mike Lewis, Hannaneh Hajishirzi, et al.2021 · 243 citations
29. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
30. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Qinyuan Ye, Bill Yuchen Lin, Xiang Ren2021 · 210 citations
31. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
32. Zero-Shot Cross-Lingual Transfer with Meta LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, et al.2020 · 171 citations
33. On Negative Interference in Multilingual Models: Findings and A Meta-Learning TreatmentConference on Empirical Methods in Natural Language Processing (EMNLP)Zirui Wang, Zachary C. Lipton, Yulia Tsvetkov2020 · 162 citations
34. Abstraction and analogy-making in artificial intelligenceMelanie Mitchell2021 · 161 citations
35. A Review on Language Models as Knowledge BasesarXiv:2204.06031Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.2022 · 150 citations
36. Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding TasksConference on Empirical Methods in Natural Language Processing (EMNLP)Zi-Yi Dou, Keyi Yu, Antonios Anastasopoulos2019 · 150 citations
37. Diverse Demonstrations Improve In-context Compositional GeneralizationAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Levy, Ben Bogin, Jonathan Berant2023 · 141 citations
38. Transformer-Patcher: One Mistake worth One NeuronarXiv:2301.09785Zeyu Huang, Yikang Shen, Xiaofeng Zhang, et al.2023 · 123 citations
39. Scaling Laws for TransferarXiv:2102.01293Danny Hernandez, Jared Kaplan, Tom Henighan, et al.2021 · 118 citations
40. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
41. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
42. Automated Design of Agentic SystemsarXiv:2408.08435Shengran Hu, Cong Lu, Jeff Clune2024 · 89 citations
43. OpenAgents: An Open Platform for Language Agents in the WildarXiv:2310.10634Tianbao Xie, Fan Zhou, Zhoujun Cheng, et al.2023 · 62 citations
44. Understanding Catastrophic Forgetting in Language Models via Implicit InferencearXiv:2309.10105Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan2023 · 45 citations
45. Continual Adaptation for Efficient Machine CommunicationConference on Computational Natural Language Learning (CoNLL)Robert Hawkins, Minae Kwon, Dorsa Sadigh, et al.2020 · 38 citations
46. Latent-Optimized Adversarial Neural Transfer for Sarcasm DetectionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xu Guo, Boyang Li, Han Yu, et al.2021 · 27 citations
47. Automatic Combination of Sample Selection Strategies for Few-Shot LearningFindings of the Association for Computational LinguisticsBranislav Pecher, Ivan Srba, Maria Bielikova, et al.2026 · 15 citations
48. Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic BiasesAnnual Meeting of the Association for Computational Linguistics (ACL)Michael Y. Hu, Jackson Petty, Chuan Shi, et al.2025 · 9 citations
49. 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
50. BLUR: A Bi-Level Optimization Approach for LLM UnlearningConference of the European Chapter of the Association for Computational Linguistics (EACL)Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, et al.2026 · 4 citations
51. Kimi-Dev: Agentless Training as Skill Prior for SWE-AgentsarXiv:2509.23045Zonghan Yang, Shengjie Wang, Kelin Fu, et al.2025 · 4 citations
52. TamEdit: Trajectory-Aware Meta-Learning for Specificity-Preserving Continual Knowledge EditingAnnual Meeting of the Association for Computational Linguistics (ACL)Shiqiang Tian, Cheng Ding, Qin Chen, et al.2026 · 1 citation
53. A Novel Synthetic Dataset for Few-Shot Legal Relation Extraction in GermanLanguage Resources and Evaluation Conference (LREC)Shiva Banasaz Nouri, Elena Leitner, Julian Moreno-Schneider, et al.2026
54. Decoupling Generalization and Adaptation in Meta-Learning for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Nitin Vetcha, Binqian Xu, Dianbo Liu2026
55. Model-Agnostic Meta Learning for Class Imbalance AdaptationFindings of the Association for Computational LinguisticsHanshu Rao, Guangzeng Han, Xiaolei Huang2026
56. SpidR-Adapt: A Universal Speech Representation Model for Few-Shot AdaptationAnnual Meeting of the Association for Computational Linguistics (ACL)Mahi Luthra, Jiayi Shen, Maxime Poli, et al.2026
57. Toward Cognitive Alignment in Large Language Models: Integrating Linguistic Theory and Human DataWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Wajdi Zaghouani2026

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