Research map / Label-efficient and robust learning / Zero-/few-shot and meta-learning
Set-based Meta-Interpolation for Few-Task Meta-Learning
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Meta-Learning with Fewer Tasks through Task Interpolation (ICLR 2022 · similarity 0.92)
- Improving Generalization in Meta-learning via Task Augmentation (ICML 2021 · similarity 0.89)
- Meta-Learning without Memorization (ICLR 2020 · similarity 0.89)
- Task Agnostic Meta-Learning for Few-Shot Learning (CVPR 2019 · similarity 0.88)
- Meta-Learning Requires Meta-Augmentation (NeurIPS 2020 · similarity 0.88)
- Unsupervised Meta-Learning via In-Context Learning (ICLR 2025 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
