Position Forcing recovers token positions from VecSet latents and quantizes them progressively, reaching best or tied-best ULIP and Uni3D scores for single-stage 3D generation
Observing that VecSet latent tokens retain recoverable spatial correspondences, the work proposes Position Forcing: during denoising it recovers token positions from the predicted clean latent, quantizes them at progressively finer resolutions according to the noise level, and feeds them back to the diffusion Transformer through 3D RoPE, providing coarse-to-fine spatial guidance for single-stage 3D generation without a separate position generation stage and achieving best or tied-best results on all four ULIP and Uni3D metrics.