Trace2Tower: Transition-Aware EigenTrace Induction of Multi-Level Skills for LLM Agents
Large language model agents increasingly rely on execution traces to master complex interactive tasks. However, current paradigms are bottlenecked by shallow trajectory retrieval and flat skill summarization, fundamentally ignoring the temporal dependencies and outcome-conditioned topology of agent behavior. We introduce Trace2Tower, a transition-aware EigenTrace framework that distills raw trajectories into a robust skill hierarchy. Trace2Tower abstracts step-level interactions into canonical events, constructing a unified graph governed by semantic compatibility, transition dynamics, and out
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- FuzzySimilar title/name (fuzzy) · 87%NirDiamant/GenAI_Agents →
“Fuzzy title match (0.94): “Trace2Tower: Transition-Aware EigenTrace Induction of Multi-” ≈ “NirDiamant/GenAI_Agents””
- FuzzySimilar title/name (fuzzy) · 84%Unity-Technologies/ml-agents →
“Fuzzy title match (0.92): “Trace2Tower: Transition-Aware EigenTrace Induction of Multi-” ≈ “Unity-Technologies/ml-agents””
- FuzzyOverlapping authors or contributors · 62%google-research/google-research →
“Shared author/contributor keys: sun”
- FuzzySimilar title/name (fuzzy) · 59%datawhalechina/hello-agents →
“Fuzzy title match (0.73): “Trace2Tower: Transition-Aware EigenTrace Induction of Multi-” ≈ “datawhalechina/hello-agents””
- FuzzySimilar title/name (fuzzy) · 59%jnMetaCode/agency-agents-zh →
“Fuzzy title match (0.73): “Trace2Tower: Transition-Aware EigenTrace Induction of Multi-” ≈ “jnMetaCode/agency-agents-zh””
- LinkedLinked via arxiv author · 85%Jiazheng Sun →
“Trace2Tower: Transition-Aware EigenTrace Induction of Multi-Level Skills for LLM Agents”
- LinkedLinked via arxiv author · 85%Boyu Yang →
“Trace2Tower: Transition-Aware EigenTrace Induction of Multi-Level Skills for LLM Agents”
- LinkedLinked via arxiv author · 85%Binhao Yuan →
“Trace2Tower: Transition-Aware EigenTrace Induction of Multi-Level Skills for LLM Agents”