Extended Data Fig. 6: Detailed performance comparison between ‘LLM4SD’ and nine baselines in the quantum mechanics domain.
From: Large language models for scientific discovery in molecular property prediction
The red dashed line shows the average result across all methods. The quantum mechanics domain includes the QM9 datasets with 12 subtasks, comprising 133,885 instances. Each marker’s error bar denotes the method’s standard deviation, which is obtained via 10 runs (n=10). These data points are overlaid on the plot in grey colour. LLM4SD excelled in predicting properties such as U0, U, H, and G, showing substantial enhancements. In other tasks, the results from LLM4SD were comparable to the average of all methods.
