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SUMMARY:Pitfalls in Evaluation of Multilingual Text Representations - Gora
 n Glavaš
DTSTART:20201203T110000Z
DTEND:20201203T120000Z
UID:TALK154558@talks.cam.ac.uk
CONTACT:Marinela Parovic
DESCRIPTION:Multilingual representation spaces\, spanned by multilingual w
 ord embeddings or massively multilingual transformers\, conceptually enabl
 e modeling of meaning across a wide range of languages and language transf
 er of task-specific NLP models from resource-rich to resource-lean languag
 es. It is not yet clear\, however\, to which extent this conceptual promis
 e holds in practice. Recent models\, both cross-lingual word embedding mod
 els and multilingual transformers\, have been praised for being able to in
 duce multilingual representation spaces without any explicit supervision (
 i.e.\, without any word-level alignments or parallel corpora). In this tal
 k\, I will point to some prominent shortcomings and pitfalls of existing e
 valuations of multilingual representation spaces\, which mask important li
 mitations of state-of-the-art multilingual representation models. Remedyin
 g for some of these evaluation shortcomings\, portrays meaning representat
 ion and language transfer capabilities of current state-of-the-art multili
 ngual representation spaces in a less favorable light.
LOCATION:https://teams.microsoft.com/l/meetup-join/19%3ameeting_YmQyY2ViND
 gtZDE1MC00MzZhLWFjZGItOWFmMjM2OTI1ZDQy%40thread.v2/0?context=%7b%22Tid%22%
 3a%2249a50445-bdfa-4b79-ade3-547b4f3986e9%22%2c%22Oid%22%3a%2230bfe2fc-889
 6-487c-84f2-f4b8875a60b2%22%7d
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