The paper introduces compositional interpretability as a category-theoretic framework that casts mechanistic explanations as commuting syntactic-semantic mappings optimized under faithfulness and complexity constraints derived from minimum description length.
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2 Pith papers cite this work, alongside 12 external citations. Polarity classification is still indexing.
2
Pith papers citing it
12
external citations · external index
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Discrete probabilistic program inference is fixed-parameter tractable under bounded treewidth of primal graphs and exponentially bounded inverse acceptance probability.
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From Mechanistic to Compositional Interpretability
The paper introduces compositional interpretability as a category-theoretic framework that casts mechanistic explanations as commuting syntactic-semantic mappings optimized under faithfulness and complexity constraints derived from minimum description length.
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Fixed-parameter tractable inference for discrete probabilistic programs, via string diagram algebraisation
Discrete probabilistic program inference is fixed-parameter tractable under bounded treewidth of primal graphs and exponentially bounded inverse acceptance probability.