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Adams Wei

As seen in: arXiv
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Articles by Adams Wei

Rethinking generative image pretraining: How far are we from scaling up next-pixel prediction?

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By Adams Wei
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2310.01798] Large Language Models Cannot Self-Correct Reasoning Yet

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By Huaixiu Steven, Adams Wei
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (270) Issue with article?

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

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By Sang Michael, Adams Wei
| arXiv
arXiv:2305.10429 (cs) [Submitted on 17 May 2023 (v1), last revised 24 May 2023 (this version, v2)] Download a PDF of the paper titled DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining, by Sang Michael Xie and 9 other authors Download PDF Submission history From: Sang Michael Xie [ view email] [v1] Wed, 17 May 2023 17:58:13 UTC (8,260 KB) [v2] Wed, 24 May 2023 05:13:10 UTC (8,261 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle...
Open in Who Shared View Duplicates (597) Issue with article?

[2109.01652] Finetuned Language Models Are Zero-Shot Learners

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By Adams Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu
| arXiv
[Submitted on 3 Sep 2021 (v1), last revised 2 Dec 2021 (this version, v4)] Authors:Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le Download PDF Abstract: This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning -- finetuning language models on a collection of tasks described via instructions -- substantially boosts zero-shot performance on unseen tasks.
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[2111.10050] Combined Scaling for Zero-shot Transfer Learning

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By Adams Wei
| arXiv
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Open in Who Shared View Duplicates (3) Issue with article?
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