AdarshSingh7647/Eklav-Math-CotGen-Data

HETU-MathReasoning-CotGen-Data Training data for the HETU (Hints Enable True Understanding) paper. Task: math reasoning (AIME, GSM8K, MATH-500, Omni-MATH, GPQA-Diamond, MMLU) Method: CotGen Examples: 3,481 train / 35-36 held-out val Format: ShareGPT (system + conversations: [{from, value}]), used for LoRA SFT via LLaMA-Factory. Single-turn ShareGPT conversations, curated DeepSeek-R1-style math reasoning distillation. Each row: the raw math/logic problem (human turn) and the… See the full description on the dataset page: https://huggingface.co/datasets/AdarshSingh7647/Eklav-Math-CotGen-Data.