Papers Molecule Captioning
“Molecule Captioning” 태그가 달린 논문 29편 · 필터 해제
From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery
Molecule discovery serves as a cornerstone in numerous scientific domains, fueling the development of new materials and innovative drug designs. Recent developments of in-silico molecule discovery have highlighted the pr…
DescriptiveDomain AdaptationMolecule CaptioningRetrievalGIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
Large language models have made significant strides in natural language processing, enabling innovative applications in molecular science by processing textual representations of molecules. However, most existing languag…
Drug DiscoveryImage CaptioningLanguage ModelingLanguage Modelling+5Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
Molecule discovery plays a crucial role in various scientific fields, advancing the design of tailored materials and drugs. However, most of the existing methods heavily rely on domain experts, require excessive computat…
In-Context LearningMolecule CaptioningNatural Language UnderstandingText-based de novo Molecule Generation+1MolFM: A Multimodal Molecular Foundation Model
Molecular knowledge resides within three different modalities of information sources: molecular structures, biomedical documents, and knowledge bases. Effective incorporation of molecular knowledge from these modalities …
Cross-Modal RetrievalKnowledge GraphsmodelMolecule Captioning+3MolXPT: Wrapping Molecules with Text for Generative Pre-training
Generative pre-trained Transformer (GPT) has demonstrates its great success in natural language processing and related techniques have been adapted into molecular modeling. Considering that text is the most important rec…
Language ModelingLanguage ModellingMolecular Property PredictionMolecule Captioning+3Unifying Molecular and Textual Representations via Multi-task Language Modelling
The recent advances in neural language models have also been successfully applied to the field of chemistry, offering generative solutions for classical problems in molecular design and synthesis planning. These new meth…
Language ModellingMolecule CaptioningMulti-Task Learningscientific discovery+1A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language
Although artificial intelligence (AI) has made significant progress in understanding molecules in a wide range of fields, existing models generally acquire the single cognitive ability from the single molecular modality.…
Contrastive LearningCross-Modal RetrievalMolecular Property PredictionMolecule Captioning+2Graph-based Molecular Representation Learning
Molecular representation learning (MRL) is a key step to build the connection between machine learning and chemical science. In particular, it encodes molecules as numerical vectors preserving the molecular structures an…
Graph Learningmolecular representationMolecule CaptioningProperty Prediction+1Translation between Molecules and Natural Language
We present $\textbf{MolT5}$ $-$ a self-supervised learning framework for pretraining models on a vast amount of unlabeled natural language text and molecule strings. $\textbf{MolT5}$ allows for new, useful, and challengi…
Drug DiscoveryMolecule CaptioningSelf-Supervised LearningText-based de novo Molecule Generation+1