PromptHub: Enhancing Multi-Prompt Visual In-Context Learning with Locality-Aware Fusion, Concentration and Alignment | ScienceToStartup | ScienceToStartup

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References (50)

[1]

Enhancing Geometric Perception in VLMs via Translator-Guided Reinforcement Learning

2026Hao Yu, Shuning Jia et al.

[2]

OmniAlpha: A Sequence-to-Sequence Framework for Unified Multi-Task RGBA Generation

2025Hao Yu, Jiabo Zhan et al.

[3]

Learning to Pose Problems: Reasoning-Driven and Solver-Adaptive Data Synthesis for Large Reasoning Models

Founder's Pitch

"PromptHub enhances visual in-context learning by intelligently fusing and aligning multiple visual prompts, improving performance and robustness across various vision tasks."

Computer Vision•Score: 7•View PDF ↗

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PromptHub: Enhancing Multi-Prompt Visual In-Context Learning with Locality-Aware Fusion, Concentration and Alignment

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Founder's Pitch

"PromptHub enhances visual in-context learning by intelligently fusing and aligning multiple visual prompts, improving performance and robustness across various vision tasks."

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PromptHub: Enhancing Multi-Prompt Visual In-Context Learning with Locality-Aware Fusion, Concentration and Alignment

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References (50)

Founder's Pitch

"PromptHub enhances visual in-context learning by intelligently fusing and aligning multiple visual prompts, improving performance and robustness across various vision tasks."

Commercial Viability Breakdown

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