years0/multilingual-code-switching-bench

Multilingual Code-Switching & Dialectal Evaluation Benchmark (Fatima Fellowship Application) Question 1: Critical Blind Spot & Capability Gap Standard NLP benchmarks (MMLU, GSM8K, HumanEval) evaluate language models on clean, standardized, monolingual inputs. However, for billions of global speakers, everyday digital communication occurs in low-resource code-switched vernaculars (e.g., Franco-Arabic/Arabizi, Singlish, Taglish, Hinglish, Naija Pidgin, Sheng… See the full description on the dataset page: https://huggingface.co/datasets/years0/multilingual-code-switching-bench.