How Can We Elevate the Quality of Large Language Models? Meet PIT: An Implicit Self-Improvement Framework

LLMs have achieved state-of-the-art results in various complex tasks, such as math reasoning, summarization, conversations, schema induction, and domain-specific problem-solving. The success of LLMs hinges on their ability to follow instructions and align with human preferences. However, they have limitations and can produce incorrect information, reasoning errors, or unhelpful content.   Various approaches have been proposed […]

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