Author

Lukas Twist

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#machine learning May 2026

Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning

It is found that standard supervised fine-tuning can rapidly suppress valid reasoning traces, and that answer-only metrics can substantially obscure this failure: in several settings, performance conditional on valid reasoning remains high while the rate of valid reasoning falls sharply.

Lukas Twist, Helen Yannakoudakis, Jie M. Zhang · arXiv.org · 4 citations

Preprint Aug 2026

LangChoiceBench: Measuring and Explaining Programming-Language Choice in LLMs

LangChoiceBench is introduced, a project-level code-generation benchmark for measuring Python preference, recommendation-implementation consistency, and language diversity, and it is found that Python remains heavily over-selected, recommendation-implementation consistency is low, and smaller open-weight models general...

Lukas Twist, Twm Stone, Helen Yannakoudakis et al. · 0 citations