Home › Code › load_state

load_state

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

load_state appears in the code Syntology harvested for 19 papers, as 19 distinct code bodies found in 21 places (a place is one code body under one paper). At least one of them ran in 3 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 load_state 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 19 distinct code bodies named load_state; 16 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
1ran
16unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 6 of the 21 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

19 papers shown of 19, newest first; 21 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. 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
Deep Learning for Protein Complex Prediction and Design by added by Syntology 2026-05 (from id) zw2x/glinter/glinter/models/checkpoint_utils.py e43485c8156c2335 unverified no licence file found · pointer only
The Format Tax added by Syntology 2026-04 (from id) ivnle/the-format-tax/judge_openai.py 87f8ee9796f65776 unverified licence not identified · pointer only
AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders 28 Jan 2025 stanfordnlp/axbench/axbench/scripts/inference.py b317e7c17c2a0012 ran · our draft was wrong Apache-2.0 (permissive)
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization 21 Jun 2024 snu-mllab/GreedyPolicyForMOCO/agg_scripts/agg_single_example.py ef1fe8afc34b157c ran MIT (permissive)
UnMarker: A Universal Attack on Defensive Image Watermarking 14 May 2024 andrekassis/ai-watermark/modules/training.py 7a0cdb2e58105e10 unverified licence not identified · pointer only
The Victim and The Beneficiary: Exploiting a Poisoned Model to Train a Clean Model on Poisoned Data 17 Apr 2024 zixuan-zhu/vab/functions_ImageNet.py 799587a17bd0a49e unverified no licence file found · pointer only
The Victim and The Beneficiary: Exploiting a Poisoned Model to Train a Clean Model on Poisoned Data 17 Apr 2024 zixuan-zhu/vab/functions_cifar10.py 0375866c08cecb25 unverified no licence file found · pointer only
VeLO: Training Versatile Learned Optimizers by Scaling Up 17 Nov 2022 amoudgl/celo/celo/utils.py d69eb755b5da1e5c unverified MIT (permissive)
SNAKE: Shape-aware Neural 3D Keypoint Field 3 Jun 2022 zhongcl-thu/SNAKE/core/utils/common.py 3777dfeb89e049b9 unverified MIT (permissive)
Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition 9 Mar 2022 xuyu0010/ATCoN/network/util.py 74c4af6adb2aab87 unverified MIT (permissive)
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph 24 Feb 2022 revsic/torch-retriever-vc/config.py a93e65374343828b unverified MIT (permissive)
CycleMLP: A MLP-like Architecture for Dense Prediction 21 Jul 2021 revsic/tf-mlptts/config.py a93e65374343828b unverified MIT (permissive)
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network 11 Jul 2021 xuyu0010/PATAN/network/util.py 5b1ff5687e0b6042 unverified MIT (permissive)
WAFFLE: Watermarking in Federated Learning 17 Aug 2020 ssg-research/WAFFLE/src/Network.py fd1ca75051b44490 unverified Apache-2.0 (permissive)
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search 22 May 2020 revsic/tf-glow-tts/config.py a93e65374343828b unverified MIT (permissive)
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations 26 Sep 2019 cypressd1999/FYP_2021/src/train_funcs.py 203cc08d9f87f46e unverified Apache-2.0 (permissive)
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations 26 Sep 2019 cypressd1999/FYP_2021/src/tasks/train_funcs.py 87f6efb51cc0c000 unverified Apache-2.0 (permissive)
Switchable Whitening for Deep Representation Learning 22 Apr 2019 XingangPan/Switchable-Whitening/utils/common_utils.py 3189ae3bf8df668c unverified MIT (permissive)
Graph Convolutional Networks for Text Classification 15 Sep 2018 plkmo/Bible_Text_GCN/text_GCN.py 1d30b9a0ccf5a53d ran · honoured contract no licence file found · pointer only
User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks 9 Aug 2018 orashi/AlacGAN/utils/io.py 768d8998674638f6 unverified MIT (permissive)
In Defense of the Triplet Loss for Person Re-Identification 22 Mar 2017 tbmoon/facenet/models.py e07f80108977f267 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".

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