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SUMMARY:David Ifeoluwa Adelani: Scaling Multilingual Evaluation of LLMs to
  Many Languages
DTSTART:20251030T203000Z
DTEND:20251030T220000Z
UID:https://cdh.princeton.edu/events/2025/10/david-adelani/
DESCRIPTION:\n\n\n\n\n    \n        \n    \n    Watch recording:\n    \n\n
     \n\n    \n    \n    \n\n\n\n    \n\n\n\n  Free and open to the public.
 Despite the widespread adoption of Large Language Models (LLMs)\, their re
 markable capabilities remain limited to a few high-resource languages. In 
 this talk\, David Ifeoluwa Adelani will describe different approaches to s
 caling evaluation to several languages. He will describe simple strategies
  for extending multilingual evaluations by repurposing existing English da
 tasets to over 200 languages for both text (SIB-200) and speech modalities
  (Fleurs-SLU). He will also introduce IrokoBench–a human-translated benc
 hmark dataset for 17 typologically diverse low-resource African languages 
 covering three tasks: natural language inference\, mathematical reasoning
 \, and multi-choice knowledge-based question answering. The talk will conc
 lude with highlights from recent projects that make some of these challeng
 ing datasets more multicultural for visual question answering and intent d
 etection tasks\, to encourage practical usage of LLMs within the low-resou
 rce communities.Dr. David Adelani is an Assistant Professor at the McGill 
 University School of Computer Science\, a Core Academic Member at Mila - Q
 uebec AI Institute\, and a Canada CIFAR AI Chair. Before his appointment a
 t McGill University\, he was a postdoctoral and DeepMind fellow at Univers
 ity College London\, United Kingdom. He received his Ph.D. in Computer Sci
 ence from the Department of Language Science and Technology at Saarland Un
 iversity in Germany in 2023\, where he was awarded a Dr. Eduard-Martin Out
 standing Doctoral Prize. His research interests include multilingual natur
 al language processing with a focus on low-resource languages\, speech pro
 cessing\, privacy\, and safety of large language models. With over 40 publ
 ications in leading NLP and Speech Processing venues like ACL\, TACL\, EMN
 LP\, NAACL\, COLING\, and Interspeech\, he has made significant contributi
 ons to NLP for low-resource languages. Notably\, one of his publications r
 eceived the Best Paper Award (Global Challenges) at COLING 2022 for develo
 ping AfroXLMR\, a multilingual pre-trained language model for African lang
 uages. Other notable awards include an Area Chair Award at IJCNLP-AACL 202
 3 and an Outstanding Paper Award and Best Theme Paper Award at NAACL 2025.
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           \n            \n        \n    \n\n        \n    \n  \n\n\n\nhttp
 s://cdh.princeton.edu/events/2025/10/david-adelani/
LOCATION:103 Bendheim House\, 26 Prospect Ave\, Princeton\, NJ 08540
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