3D scene-centric VLMs underutilize the 3D encoder, overfit to linguistic and answer-frequency shortcuts, and the proposed 3D-RDQA dataset helps expose and mitigate this problem.
Ll3da: Visual interactive instruction tuning for omni-3d understanding reasoning and planning
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Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs
3D scene-centric VLMs underutilize the 3D encoder, overfit to linguistic and answer-frequency shortcuts, and the proposed 3D-RDQA dataset helps expose and mitigate this problem.