Home › Code › named_apply

named_apply

Syntologyentry name in harvested coderead from the graph 2026-09-24

named_apply appears in the code Syntology harvested for 32 papers, as 14 distinct code bodies found in 34 places (a place is one code body under one paper). At least one of them ran in 27 of the papers; 0 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named named_apply do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 8 of the 14 distinct code bodies named named_apply; 6 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
5ran · our draft was wrong
0ran · fixture could not drive it
3ran
6unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 9 of the 34 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

32 papers shown of 32, newest first; 34 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 5 papers added by Syntology; 2 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
Vision-Language Model Purified Semi-Supervised Semantic Segmentation for Remote Sensing Images added by Syntology 2026-02 (from id) wangshanwen001/SemiEarth/model/backbone/dinov2.py e7fcb6d9ac9deaf4 ran · our draft was wrong no licence file found · pointer only
Pixel-Perfect Visual Geometry Estimation added by Syntology 2026-01 (from id) gangweix/pixel-perfect-depth/ppd/models/depth_anything_v2/dinov2.py e7fcb6d9ac9deaf4 ran · our draft was wrong Apache-2.0 (permissive)
Distribution Matching Variational AutoEncoder added by Syntology 2025-12 (from id) sen-ye/dmvae/models/dinov2.py e7fcb6d9ac9deaf4 ran · our draft was wrong no licence file found · pointer only
BioBench: A Blueprint to Move Beyond ImageNet for Scientific ML Benchmarks added by Syntology 2025-11 (from id) samuelstevens/biobench/src/biobench/webssl.py 4f780e4405d9962a unverified MIT (permissive)
SAGE: Spatial-visual Adaptive Graph Exploration for Efficient Visual Place Recognition added by Syntology 2025-09 (from id) chenshunpeng/SAGE/backbone/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
SelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place Recognition 23 Feb 2025 Lu-Feng/SelaVPR/backbone/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
Video Depth Anything: Consistent Depth Estimation for Super-Long Videos 21 Jan 2025 DepthAnything/Video-Depth-Anything/video_depth_anything/dinov2.py e7fcb6d9ac9deaf4 ran · our draft was wrong Apache-2.0 (permissive)
Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimation 18 Dec 2024 DepthAnything/PromptDA/torchhub/facebookresearch_dinov2_main/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong Apache-2.0 (permissive)
Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers 13 Dec 2024 huggingface/pytorch-image-models/timm/models/_manipulate.py a5a76ed642ff8b50 unverified Apache-2.0 (permissive)
MVC-VPR: Mutual Learning of Viewpoint Classification and Visual Place Recognition 12 Dec 2024 Gucci233/MutualVPR/backbone/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong no licence file found · pointer only
EDTformer: An Efficient Decoder Transformer for Visual Place Recognition 1 Dec 2024 tong-jin01/edtformer/backbone/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos 18 Nov 2024 yunongLiu1/IKEA-Manuals-at-Work/src/IKEAVideo/featurizers/DINOv2.py b3f9e3c043416838 unverified no licence file found · pointer only
On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection 31 Oct 2024 sparklexfantasy/mm-det/models/vit/_manipulate.py cd025b18122f9a79 unverified Apache-2.0 (permissive)
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation 14 Oct 2024 LiheYoung/UniMatch-V2/model/backbone/dinov2.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension 20 Sep 2024 liuting20/MaPPER/models/backbone/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong no licence file found · pointer only
SelEx: Self-Expertise in Fine-Grained Generalized Category Discovery 26 Aug 2024 sarahrastegar/selex/models/vision_transformer2.py e9858e26f4c51e98 ran MIT (permissive)
Mixture of Nested Experts: Adaptive Processing of Visual Tokens 29 Jul 2024 usryokousha/mone-pytorch/mone_pytorch/models/vision_transformer.py dbdf6fbba8af2996 unverified MIT (permissive)
MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models 17 Jul 2024 jiutian-vl/mome/models/dinov2_models/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
Accessing Vision Foundation Models at ImageNet-level Costs 15 Jul 2024 bespontaneous/proteus-pytorch/pretrain/models_clip.py 7ebead3a3a2008d4 ran MIT (permissive)
Depth Anything V2 13 Jun 2024 DepthAnything/Depth-Anything-V2/depth_anything_v2/dinov2.py e7fcb6d9ac9deaf4 ran · our draft was wrong Apache-2.0 (permissive)
Depth Anything V2 13 Jun 2024 fabio-sim/Depth-Anything-ONNX/depth_anything_v2/dinov2.py e1b62c034a7d44aa unverified Apache-2.0 (permissive)
LocLLM: Exploiting Generalizable Human Keypoint Localization via Large Language Model 7 Jun 2024 kennethwdk/LocLLM/models/dino.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining 20 Mar 2024 cuzyoung/crossearth/CrossEarth/models/backbones/dino_v2.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition 29 Feb 2024 Lu-Feng/CricaVPR/backbone/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers 19 Feb 2024 mrkshllr/bixt/timm/models/bixt.py 5cb5ef5a1ebc83fa ran · our draft was wrong licence not identified · pointer only
Learning Anatomically Consistent Embedding for Chest Radiography 1 Dec 2023 jlianglab/peac/models/VisionTransformer.py 6cb4da90fc7fbdd1 ran licence not identified · pointer only
Three Pillars improving Vision Foundation Model Distillation for Lidar 26 Oct 2023 valeoai/scalr/models/dinov2_vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong no licence file found · pointer only
Vision Transformers Need Registers 28 Sep 2023 facebookresearch/dinov2/dinov2/models/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong Apache-2.0 (permissive)
DINOv2: Learning Robust Visual Features without Supervision 14 Apr 2023 beneroth13/dinov2/dinov2/models/vision_transformer.py e7fcb6d9ac9deaf4 ran · our draft was wrong Apache-2.0 (permissive)
DINOv2: Learning Robust Visual Features without Supervision 14 Apr 2023 ByungKwanLee/Causal-Unsupervised-Segmentation/models/dinov2vit.py 764b0f3c664386a8 ran · our draft was wrong no licence file found · pointer only
Safe Self-Refinement for Transformer-based Domain Adaptation 16 Apr 2022 tsun/SSRT/model/SSRT.py 75e11c702145c5c3 ran · our draft was wrong MIT (permissive)
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale 22 Oct 2020 OML-Team/open-metric-learning/oml/models/vit_dino/external_v2/vision_transformer.py 3e92d5b816f50e2e ran · our draft was wrong Apache-2.0 (permissive)
arXiv:openreview_eDlsO4kFaX KiiSooo/CODiff/dinov2/dinov2_model/pre_dino.py e7fcb6d9ac9deaf4 ran · our draft was wrong MIT (permissive)
arXiv:openreview_YA3AvVx2Ze lytang63/CoGe-GCD/models/vision_transformer2.py e9858e26f4c51e98 ran MIT (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections