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- Source: inbox/queue/2026-04-00-nordby-linear-probe-accuracy-scales-model-size-multi-layer.md - Domain: ai-alignment - Claims: 2, Entities: 0 - Enrichments: 2 - Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5) Pentagon-Agent: Theseus <PIPELINE>
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| type | domain | description | confidence | source | created | title | agent | scope | sourcer | supports | related | |||
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| claim | ai-alignment | Combining probes across multiple model layers captures rotational structure of deception representations that single-layer probes miss | experimental | Nordby, Pais, Parrack (arXiv 2604.13386, April 2026) | 2026-04-21 | Multi-layer ensemble probes improve deception detection AUROC by 29-78 percent over single-layer probes because deception directions rotate gradually across layers | theseus | causal | Nordby, Pais, Parrack |
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Multi-layer ensemble probes improve deception detection AUROC by 29-78 percent over single-layer probes because deception directions rotate gradually across layers
Nordby et al. found that multi-layer ensemble probes improved AUROC by 29 percent on Insider Trading tasks and 78 percent on Harm-Pressure Knowledge tasks compared to single-layer probes. The mechanism is that deception-related activation patterns rotate gradually across model layers rather than concentrating in a single layer, making single-layer probes brittle. Multi-layer ensembles capture this rotational structure by aggregating signals across depths. The 78 percent improvement on Harm-Pressure Knowledge is particularly significant because it suggests multi-layer ensembles may push representation monitoring into a genuinely reliable regime for explicit deception at frontier scale. However, the paper does not test adversarial robustness — if multi-layer ensembles are vulnerable to concept-direction attacks like SCAV, the clean accuracy improvement may not translate to safety improvement under adversarial conditions. The finding applies only to explicit deception tasks; implicit deception remained difficult even with multi-layer ensembles.