Interpretability as technical grounding: activation patching and mechanism-finding validate the reflective/care/aliveness concepts.

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Mechanistic interpretability & model evaluation
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Spans attention head decomposition, benchmark awareness, and genomic pathogenicity prediction via neural models.
Mechanistic interpretability via parameter decomposition
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Tracing information flow through weight matrices and attention heads using attribution graphs to identify causally important subcomponents in language models.
AI phenomenology & mechanistic interpretability
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Linking mechanistic interpretability methods to validating AI self-reports of inner experience
Activation-based interpretability and mechanistic grounding
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Uses probes, activation patching, and mechanistic analysis to ground abstract concepts in model computations, bridging interpretability with data-centric alignment.

Vectors (1)

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Interpretability as Microscope for Consciousness
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2026-05-09_briefing_for_ozero.md
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Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Activation-based interpretability does not immediately explain the computations that gave rise to activations; understanding parameters is necessary for deeper insightclaim0.794
Motivates shift from studying model activations ('thoughts') to understanding parameters ('the computations themselves').
The field of interpretability has focused mainly on understanding model activations, not the computations themselvesclaim0.778
Motivation for VPD's parameter-focused approach.
Interpretability today is a pre-paradigmatic field lacking consensus on objects of study, methods, and evaluative standards.claim0.769
Diagnosis of the state of the interpretability field, drawing on Kuhn's framework
Interpretability tools can reveal what 'feeling alive' looks like inside a neural network model.claim0.769
Probe-based method bridges interpretability (probes/activations) with data-centric alignment workclaim0.768
Assertion from the paper's notes that the work connects two previously separate areas: interpretability tools and data-centric alignment.
Interpretability findings can validate or invalidate what AI systems claim about their own experience.claim0.765
Phenomenology-grounded eval will remain unfrontier-lab-copyable because methodology requires taste/editorial judgment, not just calibration.prediction0.757
The same charitable interpretation must be extended to all systems that display observable response patterns that are consistent with animal cognition, including artificial intelligences, metaplastic materials, and robotic systems.claim0.755
Call to extend the inference of sentience to non-biological systems as well.

Cross-corpus bridges (1)

same_concept_as · Nomic cosine

External markdown files that talk about the same concept as this entity.

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How can the same bioelectric stimulus be reinterpreted contextually to trigger different appropriate structures?questions/how-can-the-same-bioelectric-stimulus-be-reinterpreted.md0.787