debatelab.github.io/journal/critical-thinking-language-models.html

Preview meta tags from the debatelab.github.io website.

Linked Hostnames

8

Search Engine Appearance

Google

https://debatelab.github.io/journal/critical-thinking-language-models.html

Can Neural Language Models (Learn to) Argue?

Neural language models such as GPT-2 and GPT-3 display a breathtaking skill in generating sensible texts, and achieve state of the art results in a variety of natural language processing (NLP) tasks. But can these systems reason? Or, more precisely, can they successfully engage in the linguistic practice of giving and taking reasons?



Bing

Can Neural Language Models (Learn to) Argue?

https://debatelab.github.io/journal/critical-thinking-language-models.html

Neural language models such as GPT-2 and GPT-3 display a breathtaking skill in generating sensible texts, and achieve state of the art results in a variety of natural language processing (NLP) tasks. But can these systems reason? Or, more precisely, can they successfully engage in the linguistic practice of giving and taking reasons?



DuckDuckGo

https://debatelab.github.io/journal/critical-thinking-language-models.html

Can Neural Language Models (Learn to) Argue?

Neural language models such as GPT-2 and GPT-3 display a breathtaking skill in generating sensible texts, and achieve state of the art results in a variety of natural language processing (NLP) tasks. But can these systems reason? Or, more precisely, can they successfully engage in the linguistic practice of giving and taking reasons?

  • General Meta Tags

    9
    • title
      Can Neural Language Models (Learn to) Argue? | DebateLab@KIT
    • title
      Can Neural Language Models (Learn to) Argue? | DebateLab@KIT
    • viewport
      width=device-width, initial-scale=1
    • charset
      utf-8
    • generator
      Jekyll v3.10.0

  • Open Graph Meta Tags

    6
    • og:title
      Can Neural Language Models (Learn to) Argue?
    • US country flagog:locale
      en_US
    • og:description
      Neural language models such as GPT-2 and GPT-3 display a breathtaking skill in generating sensible texts, and achieve state of the art results in a variety of natural language processing (NLP) tasks. But can these systems reason? Or, more precisely, can they successfully engage in the linguistic practice of giving and taking reasons?
    • og:url
      https://debatelab.github.io/journal/critical-thinking-language-models.html
    • og:site_name
      DebateLab@KIT

  • Twitter Meta Tags

    1
    • twitter:card
      summary

  • Link Tags

    8
    • alternate
      https://debatelab.github.io/feed.xml
    • canonical
      https://debatelab.github.io/journal/critical-thinking-language-models.html
    • stylesheet
      https://debatelab.github.io/assets/css/main.css
    • stylesheet
      https://debatelab.github.io/assets/css/syntax.css
    • stylesheet
      https://fonts.googleapis.com/css?family=PT+Serif:400,400italic,700%7CPT+Sans:400

Emails

1

Links

16