🐦 Thread@X(Twitter) | 🐶 中文博客@知乎 | 📊 Leaderboard@PapersWithCode | 📑 BibTeX > [!IMPORTANT] > 🔥 Excited to find our DART-Math-DSMath-7B (Prop2Diff) comparable to the AIMO winner NuminaMath-7B on CoT, > but based solely on MATH & GSM8K prompt set, leaving much room to improve! > Besides, our DART method is also fully compatible with tool-integrated reasoning. > Find more details and join the discussion under this X thread! DART-Math models achieve performance superior or competitive to previous SOTAs on 2 in-domain and 4 challenging out-of-domain mathematical reasoning benchmarks, despite using much smaller datasets and no proprietary model like GPT-4. Abbreviations: College (CollegeMath), DM (DeepMind Mathematics), Olympiad (OlympiadBench-Math), Theorem (TheoremQA). Bold means the best score by SFT on the respective base model here. To reproduce our results, please refer to the DART-Math GitHub repository.* We construct our traning datasets by applying Difficulty-Aware Rejection Sampling (DARS) to the MATH and GSM8K training sets. DARS tackle severe biases towards easy queries, with frequent failures to generate any correct response for the most challenging queries, in previous…
Модальности:
Генерация текста
Области применения:
Математика
Задача: Генерация текста
Автор: hkust-nlp
Теги: llama, mathematics, en, model-index, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 20
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
