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arXiv — cs.AI

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GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents

A large language model (LLM) agent can follow more graph paths without acquiring more independent evidence. GraphEcho tests whether agents mistake these repeated encounters for additional corroboration. The benchmark varies path counts and evidential origins while holding…

arXiv — cs.AIBy: Sikun Wang, Yixi Zhou, Lei Fan, Fan ZhangSeptember 17, 2026 (Sep 17)
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AI Summary & Key Takeaways

  • A large language model (LLM) agent can follow more graph paths without acquiring more independent evidence
  • GraphEcho tests whether agents mistake these repeated encounters for additional corroboration
  • The benchmark varies path counts and evidential origins while holding…
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GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents

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