CMU's CoVeR: Training-Free Token Pruning That Preserves Multi-View 3D Reasoning in VLMs
CarnegieMellonU · hf · 2026-09-09
Carnegie Mellon researchers released CoVeR, a training-free spatial token selector for vision-language models doing multi-view 3D reasoning.
- Prunes multi-view visual tokens while enforcing exact budgets and full scene coverage
- Requires no training and preserves 3D reasoning performance
- Targets the redundancy and cost of multi-view visual token inputs in VLMs
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