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      Dear all,
      
      
      Hope you're all fine.
      
      Breaking our Summer holidays' radio silence, I'm sharing
      the paper below, with flattering news for us. My apologies
      if you have already stumbled upon it.
      
      It is a recent paper, published last July in ACL,
      in a special theme track they promoted this year,
      aimed at positive discrimination, namely at attracting
      "out of the(ir) box" papers, which would have been
      very likely rejected from ACL2020 otherwise.
      
      The key goals of this paper are "making the [ACL] community aware
      of the gap that needs to be filled before we can truly claim
      state-of-the-art technologies to be language agnostic"/universal,
      and "attempt to convince the ACL community to prioritize
      the resolution of the predicaments highlighted here,
      so that no language is left behind."
      
      One of its major, and duly emphasized, conclusion confirms
      (objectively)
      what we were (subjectively) sure about: "LREC has been more
      inclusive
      across different classes of languages" when compared
      to all the other top-tier NLP/CL venues (conferences and journal).
      
      
      All the best,
      
      António
      
      
      
      ++++++++++++++++++++++++++++++
      
      
      
      The State and Fate of Linguistic Diversity and Inclusion in the
      NLP World
      
      
      Joshi et al, 2020, acl
      
      
      
https://www.aclweb.org/anthology/2020.acl-main.560.pdf
      
      
      Language technologies contribute to promot-ing multilingualism
      and linguistic diversity around the world. However, only a very
      small number
      of the over 7000 languages of the world are represented in the
      rapidly
      evolving language technologies and applications. In this paper we
      look at
      the relation between the types of languages, resources, and
      their representation in NLP conferences to understandt he
      trajectory
      that different languages havefollowed over time. Our quantitative
      investigation underlines the disparity between languages,
      especially in terms
      of their resources, and calls into question the “language
      agnostic” status
      of current models and systems.
      
      
      
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