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tech.trivago.com | ||
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ehudreiter.com
One very positive aspect of 2023 for me was that I saw lots of really interesting research papers, much more than in previous years. Perhaps because the emergence of LLMs have encouraged some people to move away from scientifically dubious leaderboard chasing and towards more interesting research on scientific fundamentals? I describe a few of... |
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ehudreiter.com
Craig Thomson and I will present a paper at INLG on a methodology for evaluating the accuracy of generated texts, based on asking human annotators to mark up factual errors in a text. This is not cheap, but I think it is the most robust and reliable approach to measuring accuracy. |
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research.google
Posted by Bryan Perozzi, Research Scientist and Qi Zhu, Research Intern, Google Research Graph Neural Networks (GNNs) are powerful tools for levera... |
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blog.fastforwardlabs.com
This article is available as a notebook on Github. Please refer to that notebook for a more detailed discussion and code fixes and updates. Despite all the recent excitement around deep learning, neural networks have a reputation among non-specialists as complicated to build and difficult to interpret. And while interpretability remains an issue, there are now high-level neural network libraries that enable developers to quickly build neural network models without worrying about the numerical details of floating point operations and linear algebra. |
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