[N] New Contextual Calibration Method Boosts GPT-3 Accuracy Up to 30% Computer Science |
- [N] New Contextual Calibration Method Boosts GPT-3 Accuracy Up to 30%
- A high quality PRNG, so simple you can code it from memory: The Middle Square Weyl Sequence RNG
- FREE Python Programming Courses from Coursera
- BSC Numerus fixus Computing Science
- Novel Uses of Breadth-First Search
[N] New Contextual Calibration Method Boosts GPT-3 Accuracy Up to 30% Posted: 24 Feb 2021 09:49 PM PST A research team from UC Berkeley, University of Maryland and UC Irvine identifies pitfalls that cause instability in the GPT-3 language model and proposes a contextual calibration procedure that improves accuracy by up to 30 percent. Here is a quick read: New Contextual Calibration Method Boosts GPT-3 Accuracy Up to 30% The paper Calibrate Before Use: Improving Few-Shot Performance of Language Models is on arXiv. [link] [comments] |
A high quality PRNG, so simple you can code it from memory: The Middle Square Weyl Sequence RNG Posted: 24 Feb 2021 07:48 AM PST I really wanted to share this PRNG from Bernard Widynski, as many people rely on PRNGs with bad quality randomness.This one passes all statistical test and is really easy to remember:
Where
E.g.: Note that this also works with integers with different sizes, as long as the state variables are twice as large as the output variables. [link] [comments] |
FREE Python Programming Courses from Coursera Posted: 25 Feb 2021 02:04 AM PST |
BSC Numerus fixus Computing Science Posted: 25 Feb 2021 02:02 AM PST Hello!! I have applied to the University of Groningen to bsc in AI and CS, both being of the numerus fixus type and I will have the test for both this weekend. Other than a test in mathematics, they said there is no need for previous preparation. Has any of you given such a test before? I am really curious about what is the structure of a test like this ( it doesn't matter if it was for another university) [link] [comments] |
Novel Uses of Breadth-First Search Posted: 24 Feb 2021 11:22 PM PST I'm trying to create an exercise that showcases a societal use of breadth-first search? That is an application of breadth-first search that benefits society: breadth-first search helps people find transplant donors, something like that, for instance. And it can't be too obvious, like finding the optimal route from A to B or something. I haven't been able to come up with anything satisfactory despite my numerous Google searches. I would really appreciate any suggestions. [link] [comments] |
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