2026
Weights to Code: Extracting Interpretable Algorithms from the Discrete Transformer
ICML 2026poster
Algorithm extraction aims to synthesize executable programs directly from models trained on algorithmic tasks, enabling *de novo* algorithm discovery without relying on human-written code. However, applying this paradigm to Transformer is hindered by representation entanglement (e.g., superposition)…