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  2. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    There are two LLMs. One is the target LLM, and another is the prompting LLM. Prompting LLM is presented with example input-output pairs, and asked to generate instructions that could have caused a model following the instructions to generate the outputs, given the inputs. Each of the generated instructions is used to prompt the target LLM ...

  3. Few-shot learning - Wikipedia

    en.wikipedia.org/wiki/Few-shot_learning

    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)

  4. Prompt injection - Wikipedia

    en.wikipedia.org/wiki/Prompt_injection

    Prompt injection is a family of related computer security exploits carried out by getting a machine learning model which was trained to follow human-given instructions (such as an LLM) 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 ...

  5. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Concretely, one can construct an LLM that can understand images as follows: take a trained LLM, and take a trained image encoder . Make a small multilayered perceptron f {\displaystyle f} , so that for any image y {\displaystyle y} , the post-processed vector f ( E ( y ) ) {\displaystyle f(E(y))} has the same dimensions as an encoded token.

  6. Response-prompting procedures - Wikipedia

    en.wikipedia.org/wiki/Response-prompting_procedures

    The goal of response prompting is to transfer stimulus control from the prompt to the desired discriminative stimulus. [1] Several response prompting procedures are commonly used in special education research: (a) system of least prompts, (b) most to least prompting, (c) progressive and constant time delay, and (d) simultaneous prompting.

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  8. Zero-shot learning - Wikipedia

    en.wikipedia.org/wiki/Zero-shot_learning

    The name is a play on words based on the earlier concept of one-shot learning, in which classification can be learned from only one, or a few, examples. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. [1]

  9. Defense Language Institute - Wikipedia

    en.wikipedia.org/wiki/Defense_Language_Institute

    The two primary entities of the Defense Language Institute are the Defense Language Institute Foreign Language Center (DLIFLC) and the Defense Language Institute English Language Center (DLIELC). DLIFLC is located at the Presidio of Monterey in Monterey, California, and DLIELC is located at Joint Base San Antonio - Lackland Air Force Base, Texas.