Beyond Pareto: Bi-Objective and Multi-Objective Regression Trees // Implements the Bi-objective Regression Tree (BORT) for efficiently learning vector-valued functions. Unlike traditional methods that rely on constructing multiple models or static scalarisation, BORT integrates the exploration of the Pareto front directly into a single tree's growth process. It provides high-efficiency, single-model approaches that can Pareto-dominate entire Pareto-consistent families of trees, supported by a C backend for fast computation. For more details see Paz (2026) doi:10.1007/978-3-032-28393-1_2 and Paz (2025) doi:10.1007/978-3-031-78401-9_2.