---
tags:
- hetu
- mathreasoning
- cotgen
---

# 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 full teacher chain-of-thought plus a boxed final answer (gpt turn), with loss computed over the entire gpt turn.

Files:
- `train.json` -- training split
- `val.json` -- held-out validation split

See the HETU paper for full dataset construction methodology, and the corresponding
`HETU-*-MathReasoning-CotGen` model repos for checkpoints trained on this data.