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Geometry-privileged distillation improves RGB-only spatial reasoning

huggingface.co by Hongxing Li et al. Editor score 8/10

GPD routes rendered depth, semantic, and bird’s-eye-view cues to a teacher during training, while the deployed model remains RGB-only; its 4B model scores 57.1 on VSI-Bench. This offers a concrete training approach for improving spatial reasoning without adding 3D inference inputs.

What
Geometry-Privileged Distillation (GPD) trains vision-language models for spatial reasoning while keeping the deployed model RGB-only.
Method
It routes rendered depth, semantic, and BEV cues to a teacher; privileged KL on incorrect trajectories augments GRPO.
Why it matters
Training with scanned-scene geometry without 3D inference inputs offers engineers a way to improve spatial reasoning without deployment-time 3D costs.
routed as text routed as text routed as text incorrect tra… distillation depth cues semantic cues BEV cues teacher privileged KL deployed model
Rendered geometric cues inform a teacher, whose selective distillation trains the RGB-only deployed model. Sketched from the article's own text.

Read on huggingface.co → Code · 7 stars

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