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CMU Team Introduces Meta Reinforcement Fine-Tuning: A Novel Paradigm for Enhancing Large Language Model Reasoning

Large Language Models (LLMs) are constantly evolving in the field of artificial intelligence. Researchers from Carnegie Mellon University (CMU) and HuggingFace recently introduced a new method called Meta Reinforcement Fine-Tuning (MRT). This method aims to optimize the computational efficiency of LLMs during testing, particularly excelling in solving complex reasoning problems. Studies show that existing LLMs struggle with...

9.1k 21 hours ago
CMU Team Introduces Meta Reinforcement Fine-Tuning: A Novel Paradigm for Enhancing Large Language Model Reasoning

Models

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DeepSeek-R1

Deepseek

DeepSeek-R1

$4

Input tokens/M

$16

Output tokens/M

32

Context Length

o1

Openai

o1

$105

Input tokens/M

$420

Output tokens/M

200

Context Length

Qwen_v2.5_3b_Instruct

Alibaba

Qwen_v2.5_3b_Instruct

$1

Input tokens/M

-

Output tokens/M

32

Context Length

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