Research map / Label-efficient and robust learning / Zero-/few-shot and meta-learning
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
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
- Understanding Robust Generalization in Learning Regular Languages (ICML 2022 · similarity 0.91)
- Neural-Symbolic Recursive Machine for Systematic Generalization (ICLR 2024 · similarity 0.89)
- Task Generalization with Autoregressive Compositional Structure: Can Learning from $D$ Tasks Generalize to $D^T$ Tasks? (ICML 2025 · similarity 0.88)
- Scaling can lead to compositional generalization (NeurIPS 2025 · similarity 0.87)
- Consistency of Compositional Generalization Across Multiple Levels (AAAI 2025 · similarity 0.87)
- Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks (ICML 2024 · 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.