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SkillAA (Skill Abductive Attribution), a structured skill-optimization framework for frozen language models, represents skill applicability, execution, and composition in a unified graph, allowing the same structure to support skill selection, attribution-guided repair, and update validation.
This work introduces HarnessVLN, a zero-shot, training-free framework that unifies instruction-following and object-goal navigation through a shared Agent Harness, and demonstrates its applicability to both navigation tasks in real-world environments.
LookStep achieves a 49.7% success rate in VLN tasks while using significantly less data and memory than traditional methods.
