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XVR Paper Accepted To CVPR 2026 Boosts VLM Cross-View Reasoning

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Suchae Jeong@Suchaeck

🚀 Our paper "Learning Multi-View Spatial Reasoning from Cross-View Relations (XVR)" has been accepted to #CVPR2026!

Current VLMs can reason from a single view surprisingly well, but they still struggle to connect information across multiple viewpoints.

To address this, we introduce XVR: • 100K-sample VQA dataset • 3 categories, 8 tasks • Designed specifically for cross-view spatial reasoning

Most excitingly, cross-view reasoning transfers to robot manipulation. Using an XVR-trained VLM as a VLA backbone improves RoboCasa manipulation success rates by +13%p on average.

Project page: https://cross-view-relations.github.io/ Paper: https://arxiv.org/abs/2603.27967

🍿 More details below

2:36 PM · Jun 2, 2026 · 806 Views
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Kimin@kimin_le2

Introducing XVR, a new dataset for improving spatial reasoning across multiple views! We show that better spatial reasoning leads to stronger VLM backbones for VLAs. :)

If you’re interested, come chat with @Suchaeck and @Jay019374 at #CVPR2026

Suchae Jeong@Suchaeck

🚀 Our paper "Learning Multi-View Spatial Reasoning from Cross-View Relations (XVR)" has been accepted to #CVPR2026!

Current VLMs can reason from a single view surprisingly well, but they still struggle to connect information across multiple viewpoints.

To address this, we introduce XVR: • 100K-sample VQA dataset • 3 categories, 8 tasks • Designed specifically for cross-view spatial reasoning

Most excitingly, cross-view reasoning transfers to robot manipulation. Using an XVR-trained VLM as a VLA backbone improves RoboCasa manipulation success rates by +13%p on average.

Project page: https://cross-view-relations.github.io/ Paper: https://arxiv.org/abs/2603.27967

🍿 More details below

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