kalomaze: fluid cross-domain generalization hinges on composing skills end-to-end
kalomaze · x · 2026-09-07
kalomaze shares a conceptual model of deeper transfer learning ("fluid generalization across domains"): real generalization depends mostly on the need to compose independent skills from distinct domains in an end-to-end compositional process — something specific, narrow environments tend not to exercise.
More from Research
- HarnessMM cuts agent tokens per task by up to 88% while raising success rates — omarsar0 · 2026-10-26
- Ben Recht: The world needs a truly open language model, and it's easier to build than you think — beenwrekt · 2026-10-26
- New Blog Breaks Black-Box Distillation Into Five Practical Steps — chrisrohlf · 2026-10-26
- DetectorScope turns black-box AI text detectors into auditable ones with sparse autoencoders — _akhaliq · 2026-10-26
- OPST paper shows LLMs self-improve with zero human data, guided only by topic descriptions — _akhaliq · 2026-10-26
- Tencent's HiSTEVE 1.0: hierarchical VLA agent plays Minecraft with native keyboard and mouse, hits 85% SOTA — _akhaliq · 2026-10-26