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  2. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Few-shot learning [ edit ] A prompt may include a few examples for a model to learn from, such as asking the model to complete " maison → house, chat → cat, chien →" (the expected response being dog ), [ 23 ] an approach called few-shot learning .

  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. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  5. Journal of Social Work Education - Wikipedia

    en.wikipedia.org/wiki/Journal_of_Social_Work...

    The Journal of Social Work Education is a quarterly peer-reviewed academic journal dedicated to education in the fields of social work and social welfare. It was established in 1965 as the Journal of Education for Social Work, obtaining its current name in 1985. It is published by Taylor & Francis on behalf of the Council on Social Work Education.

  6. Journal of Social Work - Wikipedia

    en.wikipedia.org/wiki/Journal_of_Social_Work

    The Journal of Social Work is a peer-reviewed academic journal that covers research in the field of social work. The editor-in-chief is Steven M. Shardlow ( Keele University ). It was established in 2001 and is published by SAGE Publishing .

  7. Vicuna LLM - Wikipedia

    en.wikipedia.org/wiki/Vicuna_LLM

    Vicuna LLM is an omnibus Large Language Model used in AI research. [1] Its methodology is to enable the public at large to contrast and compare the accuracy of LLMs "in the wild" (an example of citizen science ) and to vote on their output; a question-and-answer chat format is used.

  8. Logic learning machine - Wikipedia

    en.wikipedia.org/wiki/Logic_learning_machine

    Logic learning machine (LLM) is a machine learning method based on the generation of intelligible rules. LLM is an efficient implementation of the Switching Neural Network (SNN) paradigm, [ 1 ] developed by Marco Muselli, Senior Researcher at the Italian National Research Council CNR-IEIIT in Genoa .

  9. 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]