Arxiv Papers

Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision


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The paper explores the concept of weak model supervision and its ability to elicit the full capabilities of a stronger model. The authors test this using pretrained language models and find that simple methods can improve weak-to-strong generalization, making progress on aligning superhuman models.


https://arxiv.org/abs//2312.09390


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Arxiv PapersBy Igor Melnyk

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