A multilingual large language model will reliably achieve uniform competence across all languages included in its training mixture.
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Transformer Architecture and Large Language Model Capabilities @ University of Michigan - Ann Arbor
Ch.2 Model Scaling and Capability Evaluation - Transformer Architecture and Large Language Model Capabilities @ University of Michigan - Ann Arbor
Multilingual Language Understanding on MMLU - Transformer Architecture and Large Language Model Capabilities @ University of Michigan - Ann Arbor
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A company builds a single, large-scale language model by training it on a massive dataset composed of text scraped from the public internet. During testing, the model demonstrates excellent fluency and accuracy for tasks in German, but its performance in the Irish language is poor, characterized by frequent grammatical errors and irrelevant responses. What is the most probable cause for this significant difference in performance?
Evaluating a Chatbot Development Strategy
A multilingual large language model will reliably achieve uniform competence across all languages included in its training mixture.
A development team trains a multilingual large language model on text spanning dozens of languages, but discovers that the model demonstrates poor performance when processing low-resource languages. Explain why this performance disparity occurs and identify the two critical attributes of language-specific training data that determine a model's performance in that language.