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  2. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Self-refine [33] 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: [33]

  3. 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 ...

  4. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Some examples of commonly used question answering datasets include TruthfulQA, Web Questions, TriviaQA, and SQuAD. [123] Evaluation datasets may also take the form of text completion, having the model select the most likely word or sentence to complete a prompt, for example: "Alice was friends with Bob. Alice went to visit her friend, ____". [1]

  5. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  6. File:PRcoords Cheatsheet.pdf - Wikipedia

    en.wikipedia.org/wiki/File:PRcoords_Cheatsheet.pdf

    PDF rendering of File:PRcoords_Cheatsheet.svg. Fonts work well in this copy, but all the equal signs in "=>" get copied to some not-a-character due to bad ligature handling. So if you are doing some copy-paste-to-console job, remember to fix all those places.

  7. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    A generative LLM can be prompted in a zero-shot fashion by just asking it to translate a text into another language without giving any further examples in the prompt. Or one can include one or several example translations in the prompt before asking to translate the text in question. This is then called one-shot or few-shot learning, respectively.

  8. Far-left Antifa activists waiting to see Trump actions. How ...

    www.aol.com/far-left-antifa-activists-waiting...

    Buoyed by promised pardons of their brethren for their Jan. 6 crimes and by Trump’s embrace of popular extremist far-right figures, those groups will likely see a resurgence after January ...

  9. BLOOM (language model) - Wikipedia

    en.wikipedia.org/wiki/BLOOM_(language_model)

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]