Papers with MASSIVE dataset

2 papers
MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages (2023.acl-long)

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Challenge: We present the MASSIVE dataset–Multilingual Amazon Slu resource package (SLURP) for Slot-filling, Intent classification, and Virtual assistant evaluation.
Approach: They present a 1M-example dataset of Amazon Slu utterances . they localize the dataset into 50 typologically diverse languages .
Outcome: The proposed model includes exact match accuracy, intent classification accuracy, and slot-filling F1 score.
MASSIVE-Agents: A Benchmark for Multilingual Function-Calling in 52 Languages (2025.findings-emnlp)

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Challenge: Using the original dataset, we cleaned up the MASSIVE dataset and reformatted it for evaluation within the Berkeley Function-Calling Leaderboard framework.
Approach: They present a new benchmark for assessing multilingual function calling across 52 languages . they clean the original MASSIVE dataset and reformat it for evaluation .
Outcome: The new benchmark covers 55 functions and 286 arguments in 52 languages.

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