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Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules

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Updated 5 h ago · first seen 11 Sept 2026

paper_01M294FTPMG85ZQN746EBY5N0J

Published: 11 Sept 2026; T1 · 5 h ago
arXiv: 2609.08333; T1 · 5 h ago
Category: physics.chem-ph; T1 · 5 h ago

Abstract

-cross Abstract: In molecular discovery, molecule size is coupled to composition, structure, and other target properties. Yet most 3D generators require molecule size to be specified before generation. Here, we introduce Equivariant-Free Transformer-Autoencoded Latent Flow Matching, a two-stage generative framework that relies entirely on a single fixed-dimensional molecule-level latent representation to generate variable-size molecules. The second-stage flow matching model samples this latent vector, and an autoregressive Transformer decoder then determines molecule size while generating atom types, coordinates, and chemically informative states. Canonical atom ordering and rigid-pose alignment enable standard Transformers without equivariant layers, while joint decoding of molecular geometry and an enriched chemical state enables reliable, deterministic, chemistry-guided graph recovery without requiring a learned dense pairwise bond decoder. The same fixed-dimensional latent supports unconditional and property-conditioned flow matching, while optional property supervision adds an internal ranking readout, with no separate predictor or reference calculations. On PCQM4Mv2, EF-TALFM achieves the highest fraction of molecules that are unique, training-set novel, pass sanitization and PoseBusters sanity checks, 89.4\%, compared with 75.6\% for UAE-3D and 69.8\% for FlowMol. EF-TALFM also achieves higher measured computational throughput for training and sampling. Across ten target HOMO--LUMO gaps, internal ranking doubles the density functional theory (DFT)-verified hit rate within $0.1\,\mathrm{eV}$, while preserving 97\% novelty among unique verified hits. These results demonstrate that fixed-dimensional molecule-level generation followed by symmetry-resolved autoregressive realization provides a practical architecture for open-ended and property-directed 3D molecular design.

Authors 4

Weichi Yao, Cameron Gruich, Bryan R. Goldsmith, Yixin Wang

Specification

Official page: arxiv.org/abs/2609.08333
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Arxiv announce type: replace
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
arXiv id: 2609.08333
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Categories: physics.chem-ph, cs.LG, q-bio.QM
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
PDF: arxiv.org/pdf/2609.08333
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Primary category: physics.chem-ph
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

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T19

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5 h ago

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Claim history for Official page
Value	Valid from → to	Status	Source	Confidence	Extractor
https://arxiv.org/abs/2609.08333	11 Sept 2026 21:02 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

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Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.LG	feed	T1· Official	3 h ago	1

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