US EditionGroup Reasoning Boosts AI Response Quality With Limited Tokens
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Group Reasoning Boosts AI Response Quality With Limited Tokens
Recent advances demonstrate that employing a modular thinking strategy, facilitated by the MOTIF reinforcement learning training method, enhances the reasoning capabilities of large language models like Qwen2.5, achieving up to 3.8% accuracy improvements on complex mathematical benchmarks such as MATH500 and AIME2024, while simultaneously increasing sample efficiency by utilising only 15% of training data.
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