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# Latent Quotient Evidence Training

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  1. arXiv

    Same evidence, repeated: LQET stops models from treating relays as new corroboration

    On a controlled binary benchmark with supplied report lineage, LQET makes models update beliefs by evidence provenance rather than report count, cutting new-evidence update RMSE by 41-44% and log-odds drift after eight relay steps by 89-91% relative to task-only training.

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