Research map / Label-efficient and robust learning / Zero-/few-shot and meta-learning
Sharing Knowledge for Meta-learning with Feature Descriptions
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
- Towards Automated Knowledge Integration From Human-Interpretable Representations (ICLR 2025 · similarity 0.88)
- Context-Aware Meta-Learning (ICLR 2024 · similarity 0.86)
- Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks (ICML 2024 · similarity 0.85)
- MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning (NeurIPS 2025 · similarity 0.84)
- Learning to Learn with Contrastive Meta-Objective (NeurIPS 2025 · similarity 0.84)
- Unsupervised Meta-Learning via In-Context Learning (ICLR 2025 · similarity 0.84)
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.
