pass-graph-structure-permutation-invariant-signature-text TEC-0152 · proposedPass graph structure as a permutation-invariant signature, n
Summarize sampled graph neighborhoods for an LLM agent as a fixed-length vector of named graph statistics, keeping raw text only for the top-k semantically relevant nodes, so the observation is order-independent and does not grow with neigh
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Summarize sampled graph neighborhoods for an LLM agent as a fixed-length vector of named graph statistics, keeping raw text only for the top-k semantically relevant nodes, so the observation is order-independent and does not grow with neigh Filed by the drafting stage from Multi-Agent Agentic Graph Learning via Structural Signatures (2609.09565) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Accuracy and Macro-F1 against single-agent and orchestration-based AGL baselines on four datasets (best accuracy on all four); an ablation that restores ReaGAN-style verbalized neighbors while keeping the numeric signature for collaboration routing produced the largest accuracy drop of four ablations; tokens per cross-agent message compared against serialized 1-hop/2-hop neighborhoods.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
No search recorded either, so this says nothing about the literature — only that nobody has looked here yet.
Code
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Sources
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