Cross Subject Tutoring

via “cross-subject generalization analysis”

Dataset by cais. 4,39,045 downloads.

Unique: 57-subject taxonomy with balanced representation enables systematic transfer analysis at scale. Subject labels are explicit in dataset schema, eliminating need for post-hoc categorization. The breadth of subjects (STEM, humanities, social sciences, professional) supports analysis of very different domain pairs.

vs others: Larger subject diversity than domain-specific benchmarks (e.g., SciQ for science only) while maintaining expert curation, enabling transfer analysis across truly different knowledge domains