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get_init_weights_vit

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

get_init_weights_vit appears in the code Syntology harvested for 28 papers, as 15 distinct code bodies found in 29 places (a place is one code body under one paper). At least one of them ran in 23 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 get_init_weights_vit 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 12 of the 15 distinct code bodies named get_init_weights_vit; 3 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
2ran · our draft was wrong
0ran · fixture could not drive it
10ran
3unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 10 of the 29 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

28 papers shown of 28, newest first; 29 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 2 papers added by Syntology; 1 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
Is Prompt Selection Necessary for Task-Free Online Continual Learning? added by Syntology 2026-04 (from id) efficient-learning-lab/SinglePrompt/models/singlePrompt.py f27dd436fd97776e ran · our draft was wrong MIT (permissive)
Revisiting Weight Regularization for Low-Rank Continual Learning added by Syntology 2026-02 (from id) yaoyz96/low-rank-cl/methods/ewclora.py 1c3a1d671783f6ce ran MIT (permissive)
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts 9 Jul 2025 Lain810/DCE/models/vit.py b142ce9e26ce9b4f unverified licence not identified · pointer only
Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning 28 May 2025 qhmiao/P-M-for-Continual-Learning/utils/vit_builder.py 398c127f958b7a62 ran Apache-2.0 (permissive)
Slicing Vision Transformer for Flexible Inference 6 Dec 2024 BeSpontaneous/Scala-pytorch/models_scala.py ac707dd1c89e5865 unverified MIT (permissive)
HydraViT: Stacking Heads for a Scalable ViT 26 Sep 2024 ds-kiel/HydraViT/timm/models/hydravit.py 0bbab6441363adb9 ran MIT (permissive)
Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning 17 Sep 2024 khu-agi/vil/vision_transformer.py b5dbfbeaf3d26a90 ran Apache-2.0 (permissive)
Diffusion Feedback Helps CLIP See Better 29 Jul 2024 baaivision/diva/condition/SigLIP_for_timm_models_visiontransformer.py 42d148d34d7586d4 ran MIT (permissive)
Personalized Federated Continual Learning via Multi-granularity Prompt 27 Jun 2024 skyofbeginning/fedmgp/Models/vision_transformer.py 6c600a2f0f2361f1 ran no licence file found · pointer only
ViT-1.58b: Mobile Vision Transformers in the 1-bit Era 26 Jun 2024 dlyuangod/vit-1.58b/v.py 1a1ee1200dc36a2f ran no licence file found · pointer only
Visual Prompt Tuning in Null Space for Continual Learning 9 Jun 2024 zugexiaodui/VPTinNSforCL/utils/vit_builder.py 398c127f958b7a62 ran MIT (permissive)
Dynamically Anchored Prompting for Task-Imbalanced Continual Learning 23 Apr 2024 chenxing6666/dap/vision_transformer.py 6c600a2f0f2361f1 ran no licence file found · pointer only
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation 18 Mar 2024 nus-hpc-ai-lab/dynamic-tuning/models/vision_transformer_IN21K.py 1d314401456ed7f5 unverified no licence file found · pointer only
Consistent Prompting for Rehearsal-Free Continual Learning 13 Mar 2024 Zhanxin-Gao/CPrompt/models/cprompt.py aea2fcf3341c72f6 ran · our draft was wrong no licence file found · pointer only
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection 1 Feb 2024 qinyu-allen-zhao/optfsood/model/vit_cifar.py b5dbfbeaf3d26a90 ran no licence file found · pointer only
Gradient-based Parameter Selection for Efficient Fine-Tuning 15 Dec 2023 FightingFighting/GPS/models/vision_transformer.py def23f7d7d042968 ran MIT (permissive)
ChAda-ViT : Channel Adaptive Attention for Joint Representation Learning of Heterogeneous Microscopy Images 26 Nov 2023 nicoboou/chada_vit/src/backbones/vit/vit_attn_viz.py 89b15c59ecb5d1c7 ran Apache-2.0 (permissive)
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning 18 Nov 2023 kaist-dmlab/AdaPromptCL/clip_vit.py 6c600a2f0f2361f1 ran Apache-2.0 (permissive)
Towards a General Framework for Continual Learning with Pre-training 21 Oct 2023 thu-ml/HiDe-Prompt/vits/hide_prompt_vision_transformer.py 6c600a2f0f2361f1 ran MIT (permissive)
Towards a General Framework for Continual Learning with Pre-training 21 Oct 2023 thu-ml/HiDe-Prompt/vits/hide_lora_vision_transformer.py d2462a444e3fa1df ran MIT (permissive)
On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers 18 Aug 2023 tdemin16/continual-layernorm-tuning/couple/vision_transformer.py 6c600a2f0f2361f1 ran Apache-2.0 (permissive)
Heterogeneous Forgetting Compensation for Class-Incremental Learning 7 Aug 2023 JiahuaDong/HFC/vit.py 6c600a2f0f2361f1 ran no licence file found · pointer only
Tuning Pre-trained Model via Moment Probing 21 Jul 2023 mingzeg/moment-probing/models/vision_transformer.py def23f7d7d042968 ran no licence file found · pointer only
RanPAC: Random Projections and Pre-trained Models for Continual Learning 5 Jul 2023 ranpac/ranpac/petl/vision_transformer_ssf.py def23f7d7d042968 ran MIT (permissive)
eP-ALM: Efficient Perceptual Augmentation of Language Models 20 Mar 2023 mshukor/eP-ALM/models/vit.py 6c600a2f0f2361f1 ran MIT (permissive)
Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning 17 Oct 2022 dongzelian/ssf/models/vision_transformer.py def23f7d7d042968 ran MIT (permissive)
S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning 26 Jul 2022 iamwangyabin/S-Prompts/models/vit.py b142ce9e26ce9b4f unverified MIT (permissive)
Learning to Prompt for Continual Learning 16 Dec 2021 JH-LEE-KR/l2p-pytorch/vision_transformer.py 6c600a2f0f2361f1 ran Apache-2.0 recorded; this copy not marked cleared · pointer only
arXiv:aaai_26216 iamwangyabin/ESN/models/vit.py b142ce9e26ce9b4f unverified 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".

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