From Subtle to Significant: Prompt-Driven Self-Improving Optimization in Test-Time Graph OOD Detection | ScienceToStartup | ScienceToStartup

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References (33)

[1]

Learn from Global Rather Than Local: Consistent Context-Aware Representation Learning for Multi-View Graph Clustering

2025Lele Fu, Bowen Deng et al.

[2]

Elevating Knowledge-Enhanced Entity and Relationship Understanding for Sarcasm Detection

2025Xiaobao Wang, Yujing Wang et al.

[3]

Conformal Graph-level Out-of-distribution Detection with Adaptive Data Augmentation

Founder's Pitch

"SIGOOD is an unsupervised tool for graph OOD detection, using self-improving optimization to enhance reliability in GNNs."

Graph OOD Detection•Score: 6•View PDF ↗

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From Subtle to Significant: Prompt-Driven Self-Improving Optimization in Test-Time Graph OOD Detection

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References (33)

Founder's Pitch

"SIGOOD is an unsupervised tool for graph OOD detection, using self-improving optimization to enhance reliability in GNNs."

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From Subtle to Significant: Prompt-Driven Self-Improving Optimization in Test-Time Graph OOD Detection

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References (33)

Founder's Pitch

"SIGOOD is an unsupervised tool for graph OOD detection, using self-improving optimization to enhance reliability in GNNs."

Commercial Viability Breakdown

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