# LieVLM

Multi-view 3D vision-language models suffer viewpoint-induced semantic drift: the same object and query produce weaker, diffuse or shifted target responses when the camera moves. LieVLM has geometry tokens predict local rotation parameters and channel-wise gates, applies length-preserving rotations to projected visual features within learned three-dimensional subspaces, and gates the identity-relative correction back into the original representation. On ScanRefer, LieVLM-8B reaches 64.5 Acc@0.25 and 57.2 Acc@0.5, 6.9 and 6.3 points above the published VG LLM-8B under the same proposal-refinement protocol.

Multi-view 3D vision-language models suffer viewpoint-induced semantic drift: the same object and query produce weaker, diffuse or shifted target responses when the camera moves. LieVLM has geometry tokens predict local rotation parameters and channel-wise gates, applies length-preserving rotations to projected visual features within learned three-dimensional subspaces, and gates the identity-relative correction back into the original representation. On ScanRefer, LieVLM-8B reaches 64.5 Acc@0.25 and 57.2 Acc@0.5, 6.9 and 6.3 points above the published VG LLM-8B under the same proposal-refinement protocol.