SOTAVerified

Unconditional Crystal Generation

This task evaluates the ability of generative models to sample valid and realistic crystal structures.

The training dataset, MP20 (Xie et al., 2022), contains 45,231 metastable crystal structures from the Materials Project (Jain et al., 2013), each with up to 20 atoms and spanning 89 different element types.

Following prior work (Xie et al., 2022), we sample 10,000 crystals and compute validity, stability, uniqueness and novelty rates using density functional theory (DFT). Data is generally split following prior work (Xie et al., 2022) to ensure fair comparisons.

Papers

Showing 13 of 3 papers

TitleStatusHype
All-atom Diffusion Transformers: Unified generative modelling of molecules and materialsCode3
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base DistributionsCode0
FlowMM: Generating Materials with Riemannian Flow MatchingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ADiTDFT Stable, Unique, Novel Rate6Unverified
2FlowLLMDFT Stable, Unique, Novel Rate4.7Unverified
3FlowMMDFT Stable, Unique, Novel Rate2.8Unverified