Methods › General › Normalization › LayerScale › Papers where code ran, page 1
LayerScale
Papers archive 2025-07-28
archive papers tagged: 12 · with a code link: 9 · where Syntology ran a sample: 5 (5 with a run with no instrument failure, 0 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (5 of 12 tagged: 5 with a run with no instrument failure, 0 where every run was a failure of Syntology's instrument)
Syntology We ran code from the paper's repository; we did not isolate this method inside it.
Page 1 of 1: papers 1 to 5 of the 5 tagged papers where Syntology ran at least one harvested sample (5 with a run with no instrument failure, 0 where every run was a failure of Syntology's instrument), newest first by the archive's date (ties by arXiv id). This is a filter on Syntology's record ordered by date only, not a ranking; a run is not a correctness claim. A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.
Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.
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Three things everyone should know about Vision Transformers 18 Mar 2022 · 8 repositories · arXiv:2203.09795Syntology community repositories only · 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample)
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A ConvNet for the 2020s 10 Jan 2022 · 54 repositories · arXiv:2201.03545Syntology community repositories only · 57 ran (of which 39 constructed an object rather than computing a result; 49 with no instrument failure: 1 honoured, 0 violated, 48 with no contract checked; 8 where Syntology's instrument failed) · 23 unverified (of 80 harvested samples) · 12 pointer-only (licence)
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Augmenting Convolutional networks with attention-based aggregation 27 Dec 2021 · 5 repositories · arXiv:2112.13692Syntology official (archive's flag): 1 ran · 2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 2 harvested samples)
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ResMLP: Feedforward networks for image classification with data-efficient training 7 May 2021 · 19 repositories · arXiv:2105.03404Syntology community repositories only · 5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 1 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified (of 7 harvested samples)
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Going deeper with Image Transformers 31 Mar 2021 · 21 repositories · arXiv:2103.17239Syntology official: no sample here; runs from other or unrecorded repositories · 9 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 2 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified (of 11 harvested samples) · 2 pointer-only (licence)