Santhosh Anitha Boominathan

Empirical benchmarking of large language models for data science coding: a multidimensional evaluation

The LLM4DS-Benchmark is introduced and a multidimensional empirical evaluation of seven large language models is conducted, highlighting the need for multidimensional, task-aware benchmarking and suggesting that model selection for data science coding should be guided by task characteristics and practical constraints rather than aggregate success rate alone.