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pickle_load

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

pickle_load appears in the code Syntology harvested for 21 papers, as 20 distinct code bodies found in 22 places (a place is one code body under one paper). At least one of them ran in 4 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 pickle_load 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 4 of the 20 distinct code bodies named pickle_load; 16 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
4ran
16unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 22 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

21 papers shown of 21, newest first; 22 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
A Sobering Look at Tabular Data Generation via Probabilistic Circuits added by Syntology 2026-03 (from id) april-tools/tabpc/src/util.py c09fb22594aefb61 unverified Apache-2.0 (permissive)
Video-based Music Generation added by Syntology 2026-02 (from id) serkansulun/trailer-genre-classification/utils.py 55c31b5b64373d2a unverified licence not identified · pointer only
Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow 28 Feb 2025 jiaqi5598/adavib/utils.py 84b847bd3c5f6032 unverified MIT (permissive)
Starbucks: Improved Training for 2D Matryoshka Embeddings 17 Oct 2024 ielab/starbucks/retrieval/search.py f097c396bbd9036b ran Apache-2.0 (permissive)
FIRST: Faster Improved Listwise Reranking with Single Token Decoding 21 Jun 2024 gangiswag/llm-reranker/tevatron/src/tevatron/faiss_retriever/__main__.py 4d0f740bd3b8e05f ran no licence file found · pointer only
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving 20 Jun 2024 fveler/fvel/src/data_preprocess/parse_c_function_names.py 998c11de12f26b51 unverified no licence file found · pointer only
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval 29 Apr 2024 ielab/promptreps/search.py d2d5d62b9c53b6d4 ran Apache-2.0 (permissive)
Reinforcement Retrieval Leveraging Fine-grained Feedback for Fact Checking News Claims with Black-Box LLM 26 Apr 2024 jadecurl/ffrr/chat_ffrr.py de29b3b8b466ec50 ran no licence file found · pointer only
Reinforcement Retrieval Leveraging Fine-grained Feedback for Fact Checking News Claims with Black-Box LLM 26 Apr 2024 jadecurl/ffrr/ffrr_train.py 9d7ec56446e51f13 unverified no licence file found · pointer only
Exploring the Representation Power of SPLADE Models 29 Jun 2023 ielab/understanding-splade/tevatron/src/tevatron/faiss_retriever/__main__.py d5944ba894d22f55 unverified Apache-2.0 (permissive)
Towards General-Purpose Representation Learning of Polygonal Geometries 29 Sep 2022 gengchenmai/polygon_encoder/polygoncode/polygonembed/data_util.py 1ff50601c49c8240 unverified Apache-2.0 (permissive)
The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling 28 Sep 2022 lukewys/chamber-ensemble-generator/utils/file_utils.py e8b1c08cfe12d960 unverified MIT (permissive)
Compose & Embellish: Well-Structured Piano Performance Generation via A Two-Stage Approach 17 Sep 2022 slseanwu/compose_and_embellish/stage01_compose/utils.py a452b37f41bd83f1 unverified MIT (permissive)
Is BERT Robust to Label Noise? A Study on Learning with Noisy Labels in Text Classification 20 Apr 2022 uds-lsv/bert-lnl/utils.py 482640d1ff940aad unverified MIT (permissive)
Principled Exploration via Optimistic Bootstrapping and Backward Induction 13 May 2021 rrmenon10/Bootstrapped-DQN/baselines/common/misc_util.py 131bfcd55d2d25cc unverified MIT recorded; this copy not marked cleared · pointer only
Multi-Agent Trust Region Policy Optimization 15 Oct 2020 hepengli/matrpo/matrpo/common/misc_util.py 131bfcd55d2d25cc unverified MIT (permissive)
Attention on Attention for Image Captioning 19 Aug 2019 Lieberk/Paddle-AoA-Captioning/misc/utils.py 05a5570decb65f28 unverified MIT (permissive)
3D MRI brain tumor segmentation using autoencoder regularization 27 Oct 2018 trungnhanuchiha/VAE_BRATS2018/utils/utils.py 80392812b9251abe unverified MIT (permissive)
Glow: Graph Lowering Compiler Techniques for Neural Networks 2018-05 (from id) pytorch/glow/utils/download_datasets_and_models.py 0b1b9afe65c79f72 unverified Apache-2.0 (permissive)
Spectral Normalization for Generative Adversarial Networks 16 Feb 2018 Xiaoming-Yu/SingleGAN/util/util.py c4b9e0cb79abdf65 unverified MIT (permissive)
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight 2 Oct 2017 yenchenlin/rl-attack-detection/baselines/common/misc_util.py 131bfcd55d2d25cc unverified MIT recorded; this copy not marked cleared · pointer only
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention 10 Feb 2015 shaox192/NeuralGuidance/analysis/utils.py 198d90979fd0346e unverified Apache-2.0 (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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