GTR-CoT: Graph Traversal as Visual Chain of Thought for Molecular Structure Recognition
Wang et al.'s novel VLM approach using graph traversal CoT and faithful recognition principles to improve optical …...
Deep-Learning
SubGrapher: Visual Fingerprinting of Chemical Structures
Morin et al.'s method for creating molecular fingerprints directly from images using instance segmentation of functional …...
What is Optical Chemical Structure Recognition (OCSR)?
A micro-review of Optical Chemical Structure Recognition (OCSR), tracing its evolution from rule-based systems to …
αExtractor: Automatic Chemical Information Extraction from Biomedical Literature
Xiong et al.'s deep learning system for extracting chemical structures from literature images using ResNet-Transformer …...
Img2Mol: Accurate SMILES Recognition from Molecular Graphical Depictions
Clevert et al.'s two-stage CNN approach for converting molecular images to SMILES using CDDD embeddings and extensive …...
MolNexTR: A Generalized Deep Learning Model for Molecular Image Recognition
Chen et al.'s dual-stream encoder approach for robust molecular structure recognition from diverse real-world images …...
MolParser-7M and WildMol Datasets for Robust Chemical Structure Recognition
MolParser-7M is a 7.7M-pair dataset for molecule-to-text conversion, featuring real-world images and complex structures …
MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild
Fang et al.'s method for converting molecular structure images from scientific documents into machine-readable formats …...
DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training
Liu et al.'s ICLR 2025 paper introducing DenoiseVAE, which learns adaptive, atom-specific noise for better molecular …...
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
Lu et al. introduce SpaceFormer, a Transformer that models entire 3D molecular space—not just atoms—for superior …...
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
Luo et al. introduce SPHNet, using adaptive sparsity to dramatically improve SE(3)-equivariant Hamiltonian prediction …...
Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction
Fu et al. propose energy conservation as a key MLIP diagnostic and introduce eSEN, bridging test accuracy and real …...