This AI Paper from Meta and NYU Introduces Self-Rewarding Language Models that are Capable of Self-Alignment via Judging and Training on their Own Generations

Future models must receive superior feedback for effective training signals to advance the development of superhuman agents. Current methods often derive reward models from human preferences, but human performance limitations constrain this process. Relying on fixed reward models impedes the ability to enhance learning during Large Language Model (LLM) training. Overcoming these challenges is crucial […]

The post This AI Paper from Meta and NYU Introduces Self-Rewarding Language Models that are Capable of Self-Alignment via Judging and Training on their …

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