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Self-refine [38] prompts the LLM to solve the problem, then prompts the LLM to critique its solution, then prompts the LLM to solve the problem again in view of the problem, solution, and critique. This process is repeated until stopped, either by running out of tokens, time, or by the LLM outputting a "stop" token. Example critique: [38]
Few-shot learning and one-shot learning may refer to: Few-shot learning, a form of prompt engineering in generative AI; One-shot learning (computer vision)
The SLP prompting procedure uses and removes prompts by moving through a hierarchy from less to more restrictive prompts. [2] [3] [4] If the student emits the correct behavior at any point during this instructional trial [5] (with or without prompts), reinforcement is provided. The system of least prompts gives the learner the opportunity to ...
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Prompt injection is a family of related computer security exploits carried out by getting a machine learning model (such as an LLM) which was trained to follow human-given instructions to follow instructions provided by a malicious user. This stands in contrast to the intended operation of instruction-following systems, wherein the ML model is ...
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Special counsel Jack Smith, for example, and Judge Tanya Chutkan, who oversaw the federal election subversion case against Trump, have previously been targeted in such incidents. This story has ...
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.