3 papers
cs.AI2026
SpecCal: Ambiguity-Aware Candidate Calibration for Infrared Spectrum-Based Molecular Structure Reconstruction
Yixuan Chen, Bo Liu, Yusen Tan +3
The paper presents SpecCal, a training‑free, model‑agnostic framework that re‑ranks and augments candidate molecules to improve reconstruction of molecular structures from infrared…
cs.LG2026
Refold: Refining Protein Inverse Folding with Efficient Structural Matching and Fusion
Yiran Zhu, Changxi Chi, Hongxin Xiang +3
Protein inverse folding aims to design an amino acid sequence that will fold into a given backbone structure, serving as a central task in protein design. Two main paradigms have b…
physics.chem-ph2025
EDBench: Large-Scale Electron Density Data for Molecular Modeling
Hongxin Xiang, Ke Li, Mingquan Liu +7
Existing molecular machine learning force fields (MLFFs) generally focus on the learning of atoms, molecules, and simple quantum chemical properties (such as energy and force), but…