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get_fine_tuning_parameters

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

get_fine_tuning_parameters appears in the code Syntology harvested for 14 papers, as 9 distinct code bodies found in 19 places (a place is one code body under one paper). At least one of them ran in 10 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_fine_tuning_parameters 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 3 of the 9 distinct code bodies named get_fine_tuning_parameters; 6 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 2 of the 19 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

14 papers shown of 14, newest first; 19 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. 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
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion 18 Nov 2023 Boese0601/MagicDance/tool/metrics/resnet3d.py 8d57521c7b52b777 ran · our draft was wrong no licence file found · pointer only
UnIVAL: Unified Model for Image, Video, Audio and Language Tasks 30 Jul 2023 mshukor/unival/models/unival/encoders/resnext3d.py 8d57521c7b52b777 ran · our draft was wrong Apache-2.0 (permissive)
Hilbert Distillation for Cross-Dimensionality Networks 8 Nov 2022 EagleMIT/Hilbert-Distillation/model/resnet.py 8484994a54d4c487 ran · our draft was wrong MIT (permissive)
Hilbert Distillation for Cross-Dimensionality Networks 8 Nov 2022 EagleMIT/Hilbert-Distillation/models/mobilenet.py a589526093ddf86f unverified MIT (permissive)
CRIPP-VQA: Counterfactual Reasoning about Implicit Physical Properties via Video Question Answering 7 Nov 2022 thaolmk54/hcrn-videoqa/preprocess/models/densenet.py f1dd0a40f7d1ade3 unverified Apache-2.0 (permissive)
Active Contrastive Learning of Audio-Visual Video Representations 31 Aug 2020 yunyikristy/CM-ACC/models/densenet.py b934dfd4a7bd8467 unverified MIT (permissive)
Making a Case for 3D Convolutions for Object Segmentation in Videos 26 Aug 2020 sabarim/3DC-Seg/network/Resnet3d.py 8d57521c7b52b777 ran · our draft was wrong MIT (permissive)
A Comprehensive Study on Deep Learning-based Methods for Sign Language Recognition 24 Jul 2020 iliasprc/slrzoo/models/resnet3d.py 93801ecf3026ab06 ran · our draft was wrong MIT (permissive)
Supervised Contrastive Learning 23 Apr 2020 davidczy/supcon_gamma/networks/ThreeDResnet.py 49df9db56daeba4a unverified BSD-2-Clause (permissive)
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs? 10 Apr 2020 kenshohara/3D-ResNets-PyTorch/model.py c59254c1a5526d41 unverified MIT (permissive)
An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos 12 Feb 2020 identical code first harvested elsewhere 93801ecf3026ab06 ran · our draft was wrong licence of this copy not recorded
Something-Else: Compositional Action Recognition with Spatial-Temporal Interaction Networks 20 Dec 2019 joaanna/something_else/code/model/resnet3d_xl.py 93801ecf3026ab06 ran · our draft was wrong MIT (permissive)
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition 11 Dec 2019 vt-vl-lab/SDN/models/pre_act_resnet.py 93801ecf3026ab06 ran · our draft was wrong MIT (permissive)
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition 11 Dec 2019 vt-vl-lab/SDN/models/densenet.py b934dfd4a7bd8467 unverified MIT (permissive)
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition 11 Dec 2019 vt-vl-lab/SDN/models/vgg.py b7aa932088b177a2 unverified MIT (permissive)
Unsupervised Microvascular Image Segmentation Using an Active Contours Mimicking Neural Network 4 Aug 2019 shirgur/UMIS/networks/resnet.py 93801ecf3026ab06 ran · our draft was wrong Apache-2.0 (permissive)
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? 27 Nov 2017 tianhai123/3D-ResNets/models/resnet.py 93801ecf3026ab06 ran · our draft was wrong MIT (permissive)
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? 27 Nov 2017 arundhatikurup/3DResnet/models/resnet.py 8d57521c7b52b777 ran · our draft was wrong MIT (permissive)
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? 27 Nov 2017 okankop/Efficient-3DCNNs/models/resnet.py 8484994a54d4c487 ran · our draft was wrong 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