Methods › Computer Vision › Vision and Language Pre-Trained Models › SimVLM › Papers where code ran, page 1
Simple Visual Language Model
SimVLM
Papers archive 2025-07-28
archive papers tagged: 3 · with a code link: 3 · where Syntology ran a sample: 3 (3 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 (3 of 3 tagged: 3 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 3 of the 3 tagged papers where Syntology ran at least one harvested sample (3 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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CoCa: Contrastive Captioners are Image-Text Foundation Models 4 May 2022 · 6 repositories · arXiv:2205.01917Syntology 10 ran (of which 5 constructed an object rather than computing a result; 10 with no instrument failure: 2 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified (of 17 harvested samples) · 2 pointer-only (licence)
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MAGMA -- Multimodal Augmentation of Generative Models through Adapter-based Finetuning 9 Dec 2021 · 1 repository · arXiv:2112.05253Syntology official (archive's flag): 10 ran · 10 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 4 where Syntology's instrument failed) · 5 unverified (of 15 harvested samples)
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SimVLM: Simple Visual Language Model Pretraining with Weak Supervision 24 Aug 2021 · 2 repositories · arXiv:2108.10904Syntology 22 ran (of which 8 constructed an object rather than computing a result; 16 with no instrument failure: 1 honoured, 3 violated, 12 with no contract checked; 6 where Syntology's instrument failed) · 15 unverified (of 37 harvested samples) · 32 pointer-only (licence)