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The Reflexion method [68] constructs an agent that learns over multiple episodes. At the end of each episode, the LLM is given the record of the episode, and prompted to think up "lessons learned", which would help it perform better at a subsequent episode. These "lessons learned" are given to the agent in the subsequent episodes. [citation needed]
The DeepSeek-LLM series was released in November 2023. It has 7B and 67B parameters in both Base and Chat forms. The accompanying paper claimed benchmark results higher than most open source LLMs at the time, especially Llama 2. [30]: section 5 The model code was under MIT license, with DeepSeek license for the model itself. [48]
The paper introduced a new deep learning architecture known as the transformer, based on the attention mechanism proposed in 2014 by Bahdanau et al. [4] It is considered a foundational [5] paper in modern artificial intelligence, as the transformer approach has become the main architecture of large language models like those based on GPT.
According to his 1990 paper, Harnad lays out the definition of a "symbol system" relative to his defined symbol grounding problem. As defined by Harnad, a "symbol system" is "...a set of arbitrary 'physical tokens' scratches on paper, holes on a tape, events in a digital computer, etc. that are ... manipulated on the basis of 'explicit rules ...
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.
Metacognition allows for better self-reflection and allows the writer to take the material beyond the literal meaning. [9] Reflective writing can be seen as a metacognitive genre that heavily influences literacy narrative assignments due to the increased reflective thinking it applies to students.
Marcial Losada and other researchers have attempted to create a meta learning model to analyze teams and relationships. [1] A 2013 paper provided a strong critique [2] of this attempt, arguing that it was based on misapplication of complex mathematical modelling.
Thinking, Fast and Slow is a 2011 popular science book by psychologist Daniel Kahneman.The book's main thesis is a differentiation between two modes of thought: "System 1" is fast, instinctive and emotional; "System 2" is slower, more deliberative, and more logical.