arXiv (All)
open access
Using large language models to probe the limits of atom-centered structural descriptors
Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modeling. A powerful and widely-used approach can be understood as a discretization of the histogram of pair distances, triangles, etc., that results in a hi
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Using large language models to probe the limits of atom-centered structural descriptors#411051
- ATLAS: Atomic Translation & Language for Automated Structures#1077523
- Chemical site bases and average-atom potentials for the atomic cluster expansion#1129482
- Augmenting large language models with chemistry tools#16635
- Geometry-Calibrated Conformal Abstention for Language Models#146947
Record · ID 1187502
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive