SkillSandbox: Skill Verification via Dynamic Scenario Synthesis
To construct such situations, we propose SkillSandbox, a framework that dynamically synthesizes a task and its environment for each skill that are skill-relevant yet novel.
ProofPaper ↗
Key points
- Self-evolving agents distill task-solving experience into skills for future reuse, but these skills can encode incorrect procedures or non-transferable knowledge.
- It is therefore critical to verify each skill's reusability: whether its guidance remains useful beyond the experience from which it was distilled.
- Such verification requires observing how a skill affects execution in new tasks, yet existing tasks may not expose the situations where the target skill can actually be exercised.
- Further analyses examine whether these gains reflect accurate assessment of skill reusability and identify which components of SkillSandbox contribute to them.
Sources (1)
- [1]SkillSandbox: Skill Verification via Dynamic Scenario SynthesisarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 01:48 PM
To construct such situations, we propose SkillSandbox, a framework that dynamically synthesizes a task and its environment for each skill that are skill-relevant yet novel.
Self-evolving agents distill task-solving experience into skills for future reuse, but these skills can encode incorrect procedures or non-transferable knowledge.
Extractive summary: sentences quoted from the sources.
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