Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models

Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/uncertainty-guided-compositional-alignment-with-part-to-whole-semantic-representativeness-in-hyperbolic-vision-language

stale

Proof freshness: stale
Proof status: partial
Display score: 5/10
Last proof check: 2026-03-24
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 50%

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Agent Handoff

Canonical ID uncertainty-guided-compositional-alignment-with-part-to-whole-semantic-representativeness-in-hyperbolic-vision-language | Route /signal-canvas/uncertainty-guided-compositional-alignment-with-part-to-whole-semantic-representativeness-in-hyperbolic-vision-language

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/uncertainty-guided-compositional-alignment-with-part-to-whole-semantic-representativeness-in-hyperbolic-vision-language

MCP example

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source_context

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Evidence Receipt

Route status: building

Claims: 0

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models

PDF: https://arxiv.org/pdf/2603.22042v1

Repository: https://github.com/jeeit17/UNCHA.git

Source count: Pending verification

Coverage: 50%

Last proof check: 2026-03-24T21:26:51.185Z

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Subject: Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models

Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models

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