Boolformer

End-to-end symbolic regression: Directly predicts compact Boolean formulas from input-output examples, skipping the typical search-over-programs loop of symbolic regression.

Handles complex functions: Produces compact formulas for complex Boolean functions that traditional symbolic-regression methods struggle to compress.

Gene regulatory networks: Applied to modeling the dynamics of gene regulatory networks, providing a concrete real-world application beyond synthetic benchmarks.

Transformer-as-symbolic-learner: Extends the "Transformer as symbolic regression engine" line started by earlier work on equation discovery, covering the discrete-logic case.