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GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents

This story is from 2026-09-17. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.17695v1 Announce Type: new Abstract: 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…

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  1. 2026-09-17 04:00 · arXiv cs.AI
    GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents

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