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Call for Abstracts: CLARIN Annual Conference 2021

The CLARIN Annual Conference is organized for the wider Humanities and Social Sciences community in order to exchange experiences and best practices in working with the CLARIN infrastructure and to share plans for future developments. The programme will cover a range of topics, including the design, construction and operation of the CLARIN infrastructure, the data, tools and services that it contains or should contain, its actual use by researchers, teachers or interested parties, its relation to other infrastructures and projects, and the CLARIN Knowledge Sharing Infrastructure.

IMPORTANT DATES

  • 19 January 2020: Call of Abstracts issued 
  • 14 April 2021: Submission deadline
  • 30 June 2021: Notification of acceptance
  • 27 August 2021: Camera-ready submission deadline  
  • 27-29 September 2021: CLARIN Annual Conference

https://www.clarin.eu/content/call-abstracts-clarin-annual-conference-2021

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“Template of understanding”

We need a “template of understanding”… easy to say… hard to chase by probabilistic methods.

“By systematically asking these questions about all the entities and events in a story, NLP researchers can score systems’ comprehension in a principled way, probing for the world models that systems actually need

  • Spatial: Where is everything located and how is it positioned throughout the story?
  • Temporal: What events occur and when?
  • Causal: How do events lead mechanistically to other events?
  • Motivational: Why do the characters decide to take the actions they take?

For example, Pustejovsky came with QUALIA and generative lexicons in a detailed way already 20 years ago.

James Pustejovsky, Elisabetta Jezek (2017): Generative Lexicon: Integrating Theoretical and Distributional Methods. 1. Introduction to GL and Distributional Analysis. ESSLLI 2017, 7/17/2017.

https://www.technologyreview.com/2020/07/31/1005876/natural-language-processing-evaluation-ai-opinion/

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AI draws “a baby daikon radish in a tutu walking a dog”

Personally, I am more impressed by generated “an illustration of a baby daikon radish in a tutu walking a dog.””To test DALL·E’s(based on GPT-3) ability to work with novel concepts, the researchers gave it captions that described objects they thought it would not have seen before, such as “an avocado armchair” and “an illustration of a baby daikon radish in a tutu walking a dog.” In both these cases, the AI-generated images that combined these concepts in plausible ways.”https://www.technologyreview.com/…/avocado…/amp/…

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https://www.facebook.com/Prof.PhDr.Jan.Sokol/posts/2629996340412697
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https://www.facebook.com/lew.dana/posts/10212914980229193