rStar-Math: Small LLMs Can Master Math Reasoning with Self …
Jan 8, 2025 · Through 4 rounds of self-evolution with millions of synthesized solutions for 747k math problems, rStar-Math boosts SLMs' math reasoning to state-of-the-art levels.
Microsoft Research Unveils rStar-Math: Advancing Mathematical …
4 days ago · Microsoft Research unveiled rStar-Math, a framework that demonstrates the ability of small language models (SLMs) to achieve mathematical reasoning capabilities comparable to, and in some cases ...
zhentingqi/rStar - GitHub
Oct 1, 2024 · Extensive experiments across five SLMs demonstrate rStar can effectively solve diverse reasoning problems. rStar boosts GSM8K accuracy from 12.51% to 63.91% for LLaMA2-7B, from 36.46% to 81.88% for Mistral-7B, from 74.53% to 91.13% for LLaMA3-8B-Instruct.
Microsoft's new rStar-Math technique upgrades small models to ...
Jan 9, 2025 · Microsoft’s dual releases of Phi-4 and the rStar-Math paper suggest that compact, specialized models can provide powerful alternatives to the industry’s largest systems. …
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
This paper introduces rStar, a self-play mutual reasoning approach that significantly improves reasoning capabilities of small language models (SLMs) without fine-tuning or superior models. rStar decouples reasoning into a self-play mutual generation-discrimination process.
microsoft/rStar - GitHub
Jan 9, 2025 · Introduction We present rStar-Math to demonstrate that small language models (SLMs) can rival or even surpass the math reasoning capability of OpenAI o1-mini, without distillation from superior models. rStar-Math achieves this by exercising "deep thinking" through Monte Carlo Tree Search (MCTS), where a math policy SLM performs test-time search guided by an SLM-based process reward model. The ...
Microsoft rStar-Math's SLMs outshines OpenAI's o1 in Math …
Jan 10, 2025 · Microsoft enhances the capabilities of small language models (SLMs) with rStar-Math, potentially surpassing OpenAI's o1 math reasoning.
Microsoft Launches rStar-Math with 7 Billion Parame... | DeepNewz
Jan 13, 2025 · Microsoft has introduced rStar-Math, a new system designed to enhance the math reasoning capabilities of small language models (LLMs). The model, which contains 7 billion parameters, utilizes a self-evolved approach based on System 2 deep thinking, allowing it to outperform larger models like OpenAI's o1-preview in ...
Microsoft’s new rStar-Math technique upgrades small models to ...
The key to rStar-Math is that it leverages Monte Carlo Tree Search (MCTS), a method that mimics human “deep thinking” by iteratively refining step-by-step solutions to mathematical problems.
Microsoft's rStar-Math enables small language models to ace …
Jan 12, 2025 · Microsoft Research Asia has developed a training method called rStar-Math that enables small language models to match or exceed the math performance of much larger AI systems, such as OpenAI's o1-preview.
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