daniel-furman/polyglot-or-not

Are foundation LMs multilingual knowledge bases? (EMNLP 2023)

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Experimental

This project helps developers and researchers evaluate how well large language models (LLMs) recall factual information across 20 different languages. It takes a list of factual associations (like 'The capital of France is Paris') and assesses whether an LLM correctly predicts the right answer over a set of plausible false ones. The primary users are AI/ML researchers and practitioners building or evaluating multilingual LLMs.

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Use this if you need to quantitatively measure the multilingual factual knowledge of an LLM and compare its performance across various languages.

Not ideal if you cannot access vocabulary-wide probabilities from the LLM you want to evaluate (e.g., some closed-source models like GPT-4).

LLM evaluation multilingual AI natural language processing AI research model benchmarking
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
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Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Dec 08, 2023

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