Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective

Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/investigating-more-explainable-and-partition-free-compositionality-estimation-for-llms-a-rule-generation-perspective

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Proof freshness: stale
Proof status: unverified
Display score: 3/10
Last proof check: 2026-05-01
Score updated: 2026-05-01
Score fresh until: 2026-05-31
References: 0
Source count: 3
Coverage: 50%

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Canonical ID investigating-more-explainable-and-partition-free-compositionality-estimation-for-llms-a-rule-generation-perspective | Route /signal-canvas/investigating-more-explainable-and-partition-free-compositionality-estimation-for-llms-a-rule-generation-perspective

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Evidence Receipt

Route status: building

Claims: 1

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective

PDF: https://arxiv.org/pdf/2604.27340v1

Source count: 3

Coverage: 50%

Last proof check: 2026-05-01T15:05:46.730Z

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Subject: Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective

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Investigating More Explainable and Partition-Free Compositionality Estimation for LLMs: A Rule-Generation Perspective

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