Methods › Computer Vision › Generative Models › Self-Attention Guidance › Papers where code ran, page 1
Self-Attention Guidance
Papers archive 2025-07-28
archive papers tagged: 7 · with a code link: 6 · where Syntology ran a sample: 2 (2 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 (2 of 7 tagged: 2 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 2 of the 2 tagged papers where Syntology ran at least one harvested sample (2 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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CSTA: CNN-based Spatiotemporal Attention for Video Summarization 20 May 2024 · 1 repository · arXiv:2405.11905Syntology official (archive's flag): 7 ran · 7 ran (of which 7 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 7 samples that ran constructed an object rather than computing a result (of 8 harvested samples)
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Improving Sample Quality of Diffusion Models Using Self-Attention Guidance 3 Oct 2022 · 5 repositories · arXiv:2210.00939Syntology official (archive's flag): 16 ran · 19 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 3 honoured, 2 violated, 8 with no contract checked; 6 where Syntology's instrument failed) · 3 unverified (of 22 harvested samples) · 20 pointer-only (licence)