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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]
Turn this bio statement into an engaging Twitter thread about my journey as a freelancer: [Input content]. Create the outline for a four-lesson course on [gardening with native plants].
The sections are then concatenated into a single document, which is passed once more to the LLM with a prompt asking it to remove duplications between the sections. Finally, the LLM is called one last time to generate a summary for the lead section. All this internal chattiness and repeated prompting of the LLM for multiple tasks comes at a price.
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.
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 ...
As stated above, LLM outputs should not be used verbatim to expand an article. Asking an LLM for feedback on an existing article. Such feedback should never be taken at face value. Just because an LLM says something, does not make it true. But such feedback may be helpful if you apply your own judgment to each suggestion.
China's top diplomat said on Tuesday he hoped the incoming Trump administration would "make the right choice" and work with Beijing, hours after Donald Trump told reporters the COVID-19 pandemic ...
Human feedback is commonly collected by prompting humans to rank instances of the agent's behavior. [15] [17] [18] These rankings can then be used to score outputs, for example, using the Elo rating system, which is an algorithm for calculating the relative skill levels of players in a game based only on the outcome of each game. [3]