
Yuanzhi Li
Articles
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Jul 3, 2024 |
nber.org | Yuanzhi Li |David Yermack
We study companies’ decisions about holding annual shareholder meetings on-line during the Covid pandemic, and returning to classical in-person meetings post-pandemic. Among S&P 1500 companies, the frequency of virtual meetings shot up from less than 10 percent to more than 80 percent in the first year of the pandemic, with only gradual reversion to in-person meetings since then. Partisan politics has significant associations with these decisions.
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May 19, 2024 |
nph.onlinelibrary.wiley.com | Jing Wang |Yuanzhi Li |Mizanur Rahman |Jiangmen Laboratory
Fig. S1 Elevation map derived from ground survey and Shuttle Radar Topography Mission satellite data. Fig. S2 The mean seasonality of rainfall from 2000 to 2019 at the study site. Fig. S3 Percentage of data missing of PlanetScope images analyzed in this study in 2017 at the Heishiding site. Fig.
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Apr 8, 2024 |
arxiv.org | Yuanzhi Li
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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Oct 5, 2023 |
quantamagazine.org | Ben Brubaker |Yuanzhi Li
IntroductionLearning English is no easy task, as countless students well know. But when the student is a computer, one approach works surprisingly well: Simply feed mountains of text from the internet to a giant mathematical model called a neural network. That’s the operating principle behind generative language models like OpenAI’s ChatGPT, whose ability to converse coherently (if not always truthfully) on a wide range of topics has surprised researchers and the public over the past year.
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Oct 5, 2023 |
zephyrnet.com | Yuanzhi Li
IntroductionLearning English is no easy task, as countless students well know. But when the student is a computer, one approach works surprisingly well: Simply feed mountains of text from the internet to a giant mathematical model called a neural network. That’s the operating principle behind generative language models like OpenAI’s ChatGPT, whose ability to converse coherently (if not always truthfully) on a wide range of topics has surprised researchers and the public over the past year.
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