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This paper introduces PROBE, a multi-stage pipeline for diagnosing 802.11 packet captures that combines deterministic normalization, multi-run ensemble, and a verdict-aware evidence framework to produce reliable and calibrated diagnoses, outperforming single-pass LLM analysis and naive ensemble voting.
Proposes a framework for selecting complementary LLMs as proposers in ensemble systems, reformulating proposer selection as a combinatorial problem and exploring greedy algorithms for efficient performance-cost trade-offs.