Proves detection of RGG vs. ER is impossible for d ≫ (n h(p))^3 and d ≥ (1+ε)n, resolving the detection threshold conjecture in the regime p ≳ n^{-2/3}/log n.
International journal of pattern recognition and artificial intelligence , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
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An LLM-based constraint-driven pipeline is benchmarked for generating structurally valid and resilient network topologies from intents across four scenarios, with a public dataset released.
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Resolution of the Detection Threshold Conjecture for Random Geometric Graphs in the $d>n$ Regime
Proves detection of RGG vs. ER is impossible for d ≫ (n h(p))^3 and d ≥ (1+ε)n, resolving the detection threshold conjecture in the regime p ≳ n^{-2/3}/log n.
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An LLM-Based Framework for Intent-Driven Network Topology Design
An LLM-based constraint-driven pipeline is benchmarked for generating structurally valid and resilient network topologies from intents across four scenarios, with a public dataset released.