From the source
Introducing an attention-free foundation model for reasoning tasks.
Apr 11, 2025 : PromptCoT-QwQ-32B model and its training data released, achieving new state-of-the-art results.
Mar 7, 2025 : PromptCoT project launched, including the problem generation model, distilled models (PromptCoT-DS series), and associated datasets.
Overview This repository unifies two synergistic projects aimed at advancing the frontiers of mathematical and code reasoning in Large Language Models (LLMs): PromptCoT and PromptCoT-Mamba .
PromptCoT (Synthesizing Olympiad-Level Problems for Mathematical Reasoning in Large Language Models) addresses the critical challenge of acquiring high-quality, complex problems for training advanced LLMs.
It introduces a novel methodology to systematically generate Olympiad-level mathematical problems by modeling the rationale behind expert problem design.
This approach not only enhances problem diversity and difficulty but also ensures logical consistency in problem construction, providing a scalable solution for creating robust training datasets.
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