GOAL: Geometrically Optimal Alignment for Continual Generalized Category Discovery | ScienceToStartup | ScienceToStartup

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References (20)

[1]

Consistent Supervised-Unsupervised Alignment for Generalized Category Discovery

2025Jizhou Han, Shaokun Wang et al.

[2]

DualCP: Rehearsal-Free Domain-Incremental Learning via Dual-Level Concept Prototype

2025Qiang Wang, Yuhang He et al.

[3]

Happy: A Debiased Learning Framework for Continual Generalized Category Discovery

Founder's Pitch

"GOAL provides a consistent geometric structure for continual category discovery, significantly reducing forgetting and improving class discovery."

Continual Learning•Score: 5•View PDF ↗

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2.5

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GOAL: Geometrically Optimal Alignment for Continual Generalized Category Discovery

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References (20)

Founder's Pitch

"GOAL provides a consistent geometric structure for continual category discovery, significantly reducing forgetting and improving class discovery."

Commercial Viability Breakdown

🔭 Research Neighborhood

Why It Matters

Product Angle

Disruption

Product Opportunity

Author Intelligence

Research Author 1

Research Author 2

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GOAL: Geometrically Optimal Alignment for Continual Generalized Category Discovery

BUILDER'S SANDBOX

Build This Paper

Recommended Stack

Startup Essentials

References (20)

Founder's Pitch

"GOAL provides a consistent geometric structure for continual category discovery, significantly reducing forgetting and improving class discovery."

Commercial Viability Breakdown

Related Papers

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