Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills
Robot learning is splitting into two bets: policies that bake competence into frozen weights (vision-language-action, or VLA, models), and agents that write and refine their own executable skills as code. This survey organises the field around that axis of weights versus skills. Its central analytical contribution is a deep-dive that arranges code-as-policy methods by their degree of self-improvement, from zero-shot program synthesis, through closed-loop self-repair and persistent skill memory,
Record details
Published: 2 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 8 August 2026
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ethics.ai (2 August 2026), “Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills,” evidence record 17422, https://ethics.ai/record/17422 (originally published by HuggingFace Daily Papers).
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