GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models

GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/gap-mllm-geometry-aligned-pre-training-for-activating-3d-spatial-perception-in-multimodal-large-language-models

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Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-02
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 17%

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Agent Handoff

Canonical ID gap-mllm-geometry-aligned-pre-training-for-activating-3d-spatial-perception-in-multimodal-large-language-models | Route /signal-canvas/gap-mllm-geometry-aligned-pre-training-for-activating-3d-spatial-perception-in-multimodal-large-language-models

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curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/gap-mllm-geometry-aligned-pre-training-for-activating-3d-spatial-perception-in-multimodal-large-language-models

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: GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models

PDF: https://arxiv.org/pdf/2603.16461v1

Source count: Pending verification

Coverage: 17%

Last proof check: 2026-04-02T02:30:40.136Z

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Watch and verify: GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models

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Subject: GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models

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GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models

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