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Molecule Captioning
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Molecular description generation entails the creation of a detailed textual depiction illuminating the structure, properties, biological activity, and applications of a molecule based on its molecular descriptors. It furnishes chemists and biologists with a swift conduit to essential molecular information, thus efficiently guiding their research and experiments.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language
Mol-LLM: Multimodal Generalist Molecular LLM with Improved Graph Utilization
Property Enhanced Instruction Tuning for Multi-task Molecule Generation with Large Language Models
MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules
Vector-ICL: In-context Learning with Continuous Vector Representations
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining
Atomas: Hierarchical Alignment on Molecule-Text for Unified Molecule Understanding and Generation
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
Towards 3D Molecule-Text Interpretation in Language Models
InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery
MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter
BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations
From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
MolFM: A Multimodal Molecular Foundation Model
MolXPT: Wrapping Molecules with Text for Generative Pre-training
Unifying Molecular and Textual Representations via Multi-task Language Modelling
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language
Graph-based Molecular Representation Learning
Translation between Molecules and Natural Language
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.