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On Memorization of Large Language Models in Logical Reasoning
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Stronger Models are NOT Stronger Teachers for Instruction Tuning
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šŸ“Š We present ScaleQuest-Math-1M, a mathematical reasoning dataset of 1 million high-quality question-answer pairs.
šŸ”„ We propose ScaleQuest, a scalable and novel data synthesis method that utilizes small-size open-source models to generate questions from scratch.

Project Page: https://scalequest.github.io/
Dataset: dyyyyyyyy/ScaleQuest-Math
Paper: Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch (2410.18693)
HF Collection: dyyyyyyyy/scalequest-670a7dc2623c91990f28913b

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ScaleQuest
We introduce ScaleQuest, a scalable and novel data synthesis method. Project Page: https://scalequest.github.io/
GNER
We introduce GNER, a Generative Named Entity Recognition framework, which demonstrates enhanced zero-shot capabilities across unseen entity domains.

Papers 3