AUSO: Action-Level Unified Skill Optimization from Internalization to Utilization
Skills play different roles as an agent's policy evolves: they should first provide learnable knowledge, then support capability formation, and finally be invoked only when they improve individual decisions. Existing methods rarely model this lifecycle. They either keep skills outside the model, fully internalize them, or select among internalization and utilization objectives through noisy task-level success rates. Such designs fragment training and assign uniform importance to actions within the same trajectory, even though skill guidance may help some decisions while distracting others. To
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- FuzzySimilar title/name (fuzzy) · 84%liguodongiot/llm-action →
“Fuzzy title match (0.92): “AUSO: Action-Level Unified Skill Optimization from Internali” ≈ “liguodongiot/llm-action””
- FuzzyOverlapping authors or contributors · 62%google-research/google-research →
“Shared author/contributor keys: sun”
- FuzzyOverlapping authors or contributors · 62%modular/modular →
“Shared author/contributor keys: liu”
- FuzzyOverlapping authors or contributors · 62%Zeyi-Lin/HivisionIDPhotos →
“Shared author/contributor keys: lin”
- FuzzyOverlapping authors or contributors · 62%hiyouga/LlamaFactory →
“Shared author/contributor keys: lin”
- LinkedLinked via arxiv author · 85%Huizu Lin →
“AUSO: Action-Level Unified Skill Optimization from Internalization to Utilization”
- LinkedLinked via arxiv author · 85%Chengkai Huang →
“AUSO: Action-Level Unified Skill Optimization from Internalization to Utilization”
- LinkedLinked via arxiv author · 85%Tianqi Gao →
“AUSO: Action-Level Unified Skill Optimization from Internalization to Utilization”