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LoST: Level of Semantics Tokenization for 3D Shapes research paper by Adobe, 2026

Adobe · Mar 18, 2026 · Multimodal and robotics · 3 citations · 32 upvotes · unverified

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What it shows

Level-of-Semantics Tokenization (LoST) improves 3D shape generation by ordering tokens based on semantic salience and using a novel relational alignment loss for better reconstruction and efficiency.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Niladri Shekhar Dutt, Zifan Shi, Paul Guerrero and 4 more
arXiv
2603.17995 · PDF
Venue
arXiv.org
Citations
3, 2 influential · Semantic Scholar
Upvotes
32 · Hugging Face
Code
github.com/niladridutt/LoST
Lab
Adobe · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 2Sep 25, 2026
Citationsfirst count: 3Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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