1 citations · 2 across the 4 of their papers we have counts for
4 papers
MolLangData: A Large-Scale Dataset for Molecular Structure-Language Description via a Rule-Regularized Method
Feiyang Cai, Guijuan He, Yi Hu +7
Molecular function is largely determined by structure. Accurately aligning molecular structure with natural language is therefore essential for enabling large language models (LLMs…
MolLangBench: A Comprehensive Benchmark for Language-Prompted Molecular Structure Recognition, Editing, and Generation
Feiyang Cai, Jiahui Bai, Tao Tang +7
Precise recognition, editing, and generation of molecules are essential prerequisites for both chemists and AI systems tackling various chemical tasks. We present MolLangBench, a c…
Integration Flow Models
Jingjing Wang, Dan Zhang, Joshua Luo +2
Ordinary differential equation (ODE) based generative models have emerged as a powerful approach for producing high-quality samples in many applications. However, the ODE-based met…
Is GPT Powerful Enough to Analyze the Emotions of Memes?
Jingjing Wang, Joshua Luo, Grace Yang +2
Large Language Models (LLMs), representing a significant achievement in artificial intelligence (AI) research, have demonstrated their ability in a multitude of tasks. This project…