AI RESEARCH
Coarse Semantic Injection for LLM-Conditioned Structured Indoor Prediction
arXiv CS.CV
•
ArXi:2605.16832v1 Announce Type: new Large language models (LLMs) have recently been used as structured decoders for indoor understanding from 3D point-token inputs. However, point cloud encoders often under-represent thin structural elements such as doors and windows after voxelization and sparse pooling, and may miss individual furniture instances in cluttered scenes. We propose an interface-preserving semantic augmentation for LLM-conditioned structured decoding.