Concepts de base
Artificial intelligence revolutionizes molecular science through multimodal frameworks.
Résumé
Introduction to the importance of artificial intelligence in scientific research, particularly in molecular science.
Overview of multimodal frameworks for molecules that combine text and molecule data.
Discussion on model architectures, pre-training tasks, and prompting techniques for aligning text and molecules.
Applications in drug discovery, property prediction, molecule design, reaction prediction, and intelligent agents.
Challenges include data quality, benchmarking, interpretability, reasoning ability, and integration with foundation models.
Stats
"Recently, multimodal learning and Large Language Models (LLMs) have shown impressive competence in modeling and inference."
"Inspired by the success of vision-language models, it is natural to associate molecules with text description to build multimodal frameworks."
Citations
"Artificial intelligence has demonstrated immense potential in scientific research."
"Inspired by the success of vision-language models, it is natural to associate molecules with text description to build multimodal frameworks."