Computer Science > Computation and Language
arXiv:2305.11938 (cs)
[Submitted on 19 May 2023 (v1), last revised 24 May 2023 (this version, v2)]
Title:XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Authors:Sebastian Ruder,Jonathan H. Clark,Alexander Gutkin,Mihir Kale,Min Ma,Massimo Nicosia,Shruti Rijhwani,Parker Riley,Jean-Michel A. Sarr,Xinyi Wang,John Wieting,Nitish Gupta,Anna Katanova,Christo Kirov,Dana L. Dickinson,Brian Roark,Bidisha Samanta,Connie Tao,David I. Adelani,Vera Axelrod,Isaac Caswell,Colin Cherry,Dan Garrette,Reeve Ingle,Melvin Johnson,Dmitry Panteleev,Partha Talukdar
View a PDF of the paper titled XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages, by Sebastian Ruder and 26 other authors
View PDFAbstract:Data scarcity is a crucial issue for the development of highly multilingual NLP systems. Yet for many under-represented languages (ULs) -- languages for which NLP re-search is particularly far behind in meeting user needs -- it is feasible to annotate small amounts of data. Motivated by this, we propose XTREME-UP, a benchmark defined by: its focus on the scarce-data scenario rather than zero-shot; its focus on user-centric tasks -- tasks with broad adoption by speakers of high-resource languages; and its focus on under-represented languages where this scarce-data scenario tends to be most realistic. XTREME-UP evaluates the capabilities of language models across 88 under-represented languages over 9 key user-centric technologies including ASR, OCR, MT, and information access tasks that are of general utility. We create new datasets for OCR, autocomplete, semantic parsing, and transliteration, and build on and refine existing datasets for other tasks. XTREME-UP provides methodology for evaluating many modeling scenarios including text-only, multi-modal (vision, audio, and text),supervised parameter tuning, and in-context learning. We evaluate commonly used models on the benchmark. We release all code and scripts to train and evaluate models
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2305.11938 [cs.CL] |
| (orarXiv:2305.11938v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2305.11938 arXiv-issued DOI via DataCite | |
| Related DOI: | https://doi.org/10.18653/v1/2023.findings-emnlp.125 DOI(s) linking to related resources |
Submission history
From: Jonathan Clark [view email][v1] Fri, 19 May 2023 18:00:03 UTC (8,209 KB)
[v2] Wed, 24 May 2023 06:09:28 UTC (1,052 KB)
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View a PDF of the paper titled XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages, by Sebastian Ruder and 26 other authors
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