mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer
Linting Xue,Noah Constant,Adam Roberts,Mihir Kale,Rami Al-Rfou,Aditya Siddhant,Aditya Barua,Colin Raffel +7 more
- pp 483-498
TLDR
This paper proposed a multilingual variant of T5, mT5, which was pre-trained on a new Common Crawl-based dataset covering 101 languages and achieved state-of-the-art performance on many multilingual benchmarks.Abstract:
The recent “Text-to-Text Transfer Transformer” (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide variety of English-language NLP tasks. In this paper, we introduce mT5, a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages. We detail the design and modified training of mT5 and demonstrate its state-of-the-art performance on many multilingual benchmarks. We also describe a simple technique to prevent “accidental translation” in the zero-shot setting, where a generative model chooses to (partially) translate its prediction into the wrong language. All of the code and model checkpoints used in this work are publicly available.read more
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PaLM: Scaling Language Modeling with Pathways
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TL;DR: A 540-billion parameter, densely activated, Transformer language model, which is called PaLM achieves breakthrough performance, outperforming the state-of-the-art on a suite of multi-step reasoning tasks, and outperforming average human performance on the recently released BIG-bench benchmark.
Journal ArticleDOI
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
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TL;DR: BLOOM as discussed by the authors is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total).
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GPT-NeoX-20B: An Open-Source Autoregressive Language Model
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A Survey of Large Language Models
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Proceedings ArticleDOI
PaLI: A Jointly-Scaled Multilingual Language-Image Model
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