reptimeline: Tracking Discrete Representation Evolution During Neural Network Training

We present reptimeline, a Python library for tracking how discrete representations evolveduring neural network training. Unlike scalar logging tools (WandB, TensorBoard) that reportaggregate metrics, reptimeline tracks per-code lifecycle events: when concepts become distinguishable (births), when representations collapse (deaths), when relationships form betweenconcept pairs (connections), and where phase transitions occur in training dynamics. Thelibrary additionally discovers what each code element encodes—anti-correlated pairs, dependency chains, and three-way AND-gate interactions—without requiring prior ontological knowledge, with all discoveries subjected to multiple-comparison correction (Bonferroni or…