point-first-then-emit-quantized-trajectory-tokens TEC-0160 · proposedPoint first, then emit quantized trajectory tokens
Extends the VLM vocabulary with image-grid affordance/object pointing tokens and three-level residual vector-quantized action tokens, so spatial intent and precise trajectories are both decoded by the original language-model head.
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Extends the VLM vocabulary with image-grid affordance/object pointing tokens and three-level residual vector-quantized action tokens, so spatial intent and precise trajectories are both decoded by the original language-model head. Filed by the drafting stage from LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation (2608.30935) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Reported state-of-the-art monocular success rates across 10 public navigation simulation settings (R2R/RxR val-unseen, MP3D and HM3D v1/v2 ObjectNav, HM3D-OVON, EVT-Bench STT/DT) with one checkpoint and no benchmark-specific fine-tuning; the tokenizer's 0.72 cm average displacement error versus 2.48 cm for a single-level 4096-entry planning vocabulary; embodied-reasoning checkpoint scored on 8 spatial benchmarks. No ablation isolating the pointing prefix is shown in the given text.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
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