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Add news of comparability to NuminaMath-7B
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README.md

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\| 📑
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[BibTeX](https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#citation)
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> \[!IMPORTANT\]
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>
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> 🔥 **News!!!**
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>
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> - \[2024/07/21\] Excited to find **our [`DART-Math-DSMath-7B`
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> (Prop2Diff)](https://huggingface.co/hkust-nlp/dart-math-dsmath-7b-prop2diff)
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> [comparable](https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf)
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> to the AIMO winner
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> [NuminaMath-7B](https://huggingface.co/AI-MO/NuminaMath-7B-CoT)** on
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> CoT, but based solely on
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> [MATH](https://huggingface.co/datasets/hkust-nlp/dart-math-pool-math-query-info)
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> &
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> [GSM8K](https://huggingface.co/datasets/hkust-nlp/dart-math-pool-gsm8k-query-info)
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> prompt set, leaving much room to improve! Besides, our [`DART`
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> method](https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#dars--difficulty-aware-rejection-sampling)
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> is also fully [compatible with tool-integrated
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> reasoning](https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#tool-integrated-reasoning-reasoning-in-natural-language-interleaved-with-python-code).
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> Join the discussion under this [X
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> thread](https://x.com/tongyx361/status/1815112376649134172)!
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<div align="center">
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<img src="https://tongyx361.github.io/assets/dart-math/main-results.png" alt="Main results averaged on 2 in-domain and 4 challenging out-of-domain mathematical reasoning benchmarks." height=300px>

nbs/index.ipynb

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"🐦 [Thread@X(Twitter)](https://x.com/tongyx361/status/1811413243350454455) | 🐶 [中文博客@知乎](https://zhuanlan.zhihu.com/p/708371895) | 📊 [Leaderboard@PapersWithCode](https://paperswithcode.com/paper/dart-math-difficulty-aware-rejection-tuning#results) | 📑 [BibTeX](https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#citation)\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"> [!IMPORTANT]\n",
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">\n",
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"> 🔥 **News!!!**\n",
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">\n",
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"> - [2024/07/21] Excited to find **our [`DART-Math-DSMath-7B` (Prop2Diff)](https://huggingface.co/hkust-nlp/dart-math-dsmath-7b-prop2diff) [comparable](https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf) to the AIMO winner [NuminaMath-7B](https://huggingface.co/AI-MO/NuminaMath-7B-CoT)** on CoT,\n",
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"> but based solely on [MATH](https://huggingface.co/datasets/hkust-nlp/dart-math-pool-math-query-info) & [GSM8K](https://huggingface.co/datasets/hkust-nlp/dart-math-pool-gsm8k-query-info) prompt set,\n",
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"> leaving much room to improve!\n",
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"> Besides, our [`DART` method](https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#dars--difficulty-aware-rejection-sampling) is also fully [compatible with tool-integrated reasoning](https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#tool-integrated-reasoning-reasoning-in-natural-language-interleaved-with-python-code).\n",
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"> Join the discussion under this [X thread](https://x.com/tongyx361/status/1815112376649134172)!\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},

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