Answers.Body: <p>Well, you have to think that LMM are just next-token-predictors, so if you let it read a lot of text from the web/textbooks, probably they will learn that after &quot;Be brief&quot; there is a summarization of the text given before, which means to exclude certain words, to phrase stuff in a certain way and so on</p>
  <p>You might also be interested in <a href="https://arxiv.org/pdf/2208.01066.pdf#:%7E:text=Transformers%20can%20in%2Dcontext%20learn%20linear%20functions.&amp;text=Specifically%2C%20the%20trained%20model%20achieves,to%20generate%20the%20training%20prompts." rel="nofollow noreferrer">this paper</a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-10-22T16:45:27.163Z
Answers.LastActivityDate: 2023-10-22T16:45:27.163Z
Answers.UserDisplayName: Alberto
Body: <p>I don't ask how to make it summarize xy but if it is known how a &quot;LLM&quot; understands and performs this meta task at all.</p>
  <p>The same is true for prompts like &quot;Be brief&quot; or &quot;Explain in a few sentences&quot;. Since this works, the LLM must actually have an understanding of text length.</p>
  
Tags: <large-language-models><text-summarization><prompt>
Title: How can LLMs understand and perform meta tasks? (e.g. summarization)
UserDisplayName: d3nigma
ThreadText: # How can LLMs understand and perform meta tasks? (e.g. summarization)
  
  (Asked by: username_0 on 2023-10-19)
  
  I don't ask how to make it summarize xy but if it is known how a "LLM" understands and performs this meta task at all.
  
  The same is true for prompts like "Be brief" or "Explain in a few sentences". Since this works, the LLM must actually have an understanding of text length.
  
  **Tags:** large-language-models, text-summarization, prompt
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2023-10-22. Score: 2 | Accepted answer
  
  Well, you have to think that LMM are just next-token-predictors, so if you let it read a lot of text from the web/textbooks, probably they will learn that after "Be brief" there is a summarization of the text given before, which means to exclude certain words, to phrase stuff in a certain way and so on
  
  You might also be interested in [this paper](https://arxiv.org/pdf/2208.01066.pdf#:%7E:text=Transformers%20can%20in%2Dcontext%20learn%20linear%20functions.&text=Specifically%2C%20the%20trained%20model%20achieves,to%20generate%20the%20training%20prompts.)
  
  
  ---
  
  