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cs.LG2026
Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning
Lukas Twist, Helen Yannakoudakis, Jie M. Zhang
Explicit reasoning models are trained to produce intermediate reasoning traces before final answers, but downstream fine-tuning is often performed on ordinary instruction--response…
cs.LG2026
Not All Code Is Equal: A Data-Centric Study of Code Complexity and LLM Reasoning
Lukas Twist, Shu Yang, Hanqi Yan +4
Large Language Models (LLMs) increasingly exhibit strong reasoning abilities, often attributed to their capacity to generate chain-of-thought-style intermediate reasoning. Recent w…