Foundation models diversify across modalities and data structures

Tabular, relational, audiovisual, geospatial, and geometry-aware models are extending foundation-model methods beyond conventional language and image tasks. New TabPFN educational coverage is useful for explaining synthetic pretraining and distribution shift but duplicates existing reporting; broader benchmarks, independent replication, privacy analysis, and real-world deployment evaluation remain needed.