May 11, 2022 preprint Open access Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning arXiv (Cornell University) DOI: 10.48550/arxiv.2205.05638 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 1 stored of 284 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Low-Resource Vision Challenges for Foundation Models 2024 IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings conference-paper Computer Science Domain Adaptation and Few-Shot Learning Open access 11 citations 1 result References 0