claim

active

claim:interpretable-predictions-can-help-resolve-variants-of-uncertain-significance

Interpretable predictions can help resolve variants of uncertain significance

Motivating claim that mechanistic explanations add clinical value for VUS.

Source paper

extracted_from

Explaining 4.2 million genetic variants with state-of-the-art, interpretable predictions

(2026) · Pearce, Michael · Dooms, Thomas · Yamamoto, Ryo · Meehl, Joshua +18

Neighborhood — ranked by edge-count

Papers (1)

paper

Explaining 4.2 million genetic variants with state-of-the-art, interpretable predictions
mentions

Findings (1)

finding

Mechanistic explanations provided for ~2M variants of uncertain significance
supports
Scale of interpretability output, addressing a major clinical need for VUS resolution.

Communities (3)

community

Mechanistic interpretability & model evaluation
members_of
Spans attention head decomposition, benchmark awareness, and genomic pathogenicity prediction via neural models.
Mechanistic interpretability via parameter decomposition
members_of
Tracing information flow through weight matrices and attention heads using attribution graphs to identify causally important subcomponents in language models.
Convergent interpretability across neural architectures
members_of
Studies showing that learned feature representations and interpretable directions emerge consistently across different model designs and scales.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

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Interpretability findings can validate or invalidate what AI systems claim about their own experience.claim0.777
These dynamics are consistent with predictive processing since active inference prescribes dynamics that minimise prediction error.concept0.751
Connection between active inference neuronal dynamics and predictive processing theory.
interpretabilityconcept0.750
The capability to explain model predictions; a central theme of the paper, with disruption profiles as vehicle.
We evaluate the relative life of a process by making predictions based on thought-experiments or simulations.claim0.750
Patching h[1] with a divergent representation can activate distinct, hidden pathways that result in misleadingly confirmatory behavior and/or undetected behavior.quote0.749
Load-bearing description of the core pernicious divergence mechanism illustrated in Figure 1
probably helps not only with faithful reconstruction but also creates interference patterns that encode nuanced information about the deltas and convergences between states.quote0.749
Key quote connecting path redundancy to interferometric information encoding.
Interpretability Illusionconcept0.747
Cases where subspace interventions change model behaviour through parallel pathways rather than the target feature
are the resulting parameter subcomponents actually interpretable objects?question0.746
First question posed after applying VPD, investigating whether the subcomponents make sense.