CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention | ScienceToStartup | ScienceToStartup

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References (70)

[1]

Towards Unified Vision-Language Models with Incomplete Multi-Modal Inputs

2026Xiang Fang, Wanlong Fang et al.

[2]

Rethinking Video-Language Model from the Language Input Perspective

2026Xiang Fang, Wanlong Fang et al.

[3]

VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo

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"CARE enhances multi-head latent attention conversion for improved inference efficiency."

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CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention

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"CARE enhances multi-head latent attention conversion for improved inference efficiency."

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CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention

BUILDER'S SANDBOX

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Startup Essentials

References (70)

Founder's Pitch

"CARE enhances multi-head latent attention conversion for improved inference efficiency."

Commercial Viability Breakdown

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