Strawman Baseline Outperforms Complex Scheme in LLM Provenance Tests

A new experimental harness, provenance-compaction-lab, has been developed to measure the impact of provenance data compaction on LLM gate decisions. The harness compares four methods: ground truth (full data), structural_min (axis scores with compacted lineage), structural_perhop (lineage carried structurally), and prose (LLM summarization). Initial tests show that a simple strawman baseline, which uses LLM summarization for provenance, outperformed a more complex scheme on half of the tested gate classes. AI

IMPACT This research could lead to more efficient and accurate provenance tracking in LLMs, improving their reliability and interpretability.

RANK_REASON The item describes a new experimental setup for evaluating LLM provenance tracking methods, which constitutes research. [lever_c_demoted from research: ic=1 ai=1.0]

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