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BLOOMZ

26 papers tagged archive 2025-07-28

Introduced by Niklas Muennighoff et al. in Crosslingual Generalization through Multitask Finetuning

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

BLOOMZ is a Multitask prompted finetuning (MTF) variant of BLOOM.

PaperSource

Papers archive 2025-07-28

26 shown of 26, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 41 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Language Modelling6
Translation4
Zero-Shot Learning4
Diversity3
Language Modeling3
Large Language Model3
Machine Translation3
Benchmarking2
Decoder2
Few-Shot Learning2
Instruction Following2
Multi-task Language Understanding2
Multiple-choice2
Question Answering2
Sentiment Analysis2
Zero-shot Generalization2
ArabicMMLU1
Chatbot1
Coreference Resolution1
Cross-Lingual Transfer1

Usage over time archive 2025-07-28

Papers per year tagged with BLOOMZ: 2022 to 2025, peak 16 16 0 2022: 2 papers 2022 2023: 16 papers 2023 2024: 7 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (26 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Language Models

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