2 papers
cs.LG2026
Weights to Code: Extracting Interpretable Algorithms from the Discrete Transformer
Yifan Zhang, Wei Bi, Kechi Zhang +3
Algorithm extraction aims to synthesize executable programs directly from models trained on algorithmic tasks, enabling de novo recovery of executable mechanisms from weights witho…
cs.CL2025
Finite State Automata Inside Transformers with Chain-of-Thought: A Mechanistic Study on State Tracking
Yifan Zhang, Wenyu Du, Dongming Jin +2
Chain-of-thought (CoT) significantly enhances the performance of large language models (LLMs) across a wide range of tasks, and prior research shows that CoT can theoretically incr…