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cs.CL2026
The Imitation Game: When LLMs Learn to Reason Like Programs via Code-Centric Reasoning Data Synthesis
Jinyang Zhang, Weibin Liao, Keqin Bao +10
Large Language Models (LLMs) excel at programming tasks but frequently fail at deterministic, fine-grained reasoning in natural language, relying heavily on semantic approximations…
cs.CL2026
Chronos: Learning Temporal Dynamics of Reasoning Chains for Test-Time Scaling
Kai Zhang, Jiayi Liao, Chengpeng Li +3
Test-Time Scaling (TTS) has emerged as an effective paradigm for improving the reasoning performance of large language models (LLMs). However, existing methods -- most notably majo…