Before that, it is crucial to develop benchmarks to evaluate L VLMs' effectiveness in various medical applications.

Despite this remarkable progress, there is a noticeable absence of datasets that combine electrocardiogram (ECG) data with question answering.

While significant progress has been made in developing autonomous agents for shape assembly, existing datasets have not yet tackled the 4D grounding of assembly instructions in videos, essential for a holistic understanding of assembly in 3D space over time.

As quantum chemical properties have a dependence on their geometries, graph neural networks (GNNs) using 3D geometric information have achieved high prediction accuracy in many tasks.