AI Research
Resource-Efficient Reinforcement Learning Post-Training through Elastic Expert Parallelism
A major computational bottleneck in improving large language models is generating training responses.
Reinforcement learning post-training improves the capabilities of large language models, but generating training responses is a major computational bottleneck.
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ArXiv CS.AI
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ArXiv CS.AI
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Reducing the cost of generating training responses could make reinforcement learning post-training more efficient. This matters because response generation is a major computational bottleneck in efforts to improve large language models.
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