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download_url

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

download_url appears in the code Syntology harvested for 32 papers, as 18 distinct code bodies found in 34 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 download_url 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 1 of the 18 distinct code bodies named download_url; 17 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
1ran
17unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 11 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 2 papers added by Syntology; 3 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
FlashFPS: Efficient Farthest Point Sampling for Large-Scale Point Clouds via Pruning and Caching added by Syntology 2026-04 (from id) Yuzhe-Fu/FlashFPS/FlashFPS-Openpoints/openpoints/dataset/data_util.py 556e417290a6e1fd unverified licence not identified · pointer only
PruneCD: Contrasting Pruned Self Model to Improve Decoding Factuality added by Syntology 2025-09 (from id) hoeng4/PruneCD/2_benchmark/1_tfqa_gen.py 0f14b819bc361c25 unverified no licence file found · pointer only
Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models 17 Jun 2025 benfinkelshtein/equivarianceeverywhere/helpers/datasets.py f026a6607b2915ad unverified MIT (permissive)
arXiv:2504.04635 2025-04 (from id) patqdasilva/steering-off-course/DoLa/factor_eval.py 0f14b819bc361c25 unverified MIT (permissive)
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models 1 Nov 2024 JayZhang42/SLED/utils/utils_factor.py 0ce848f1f5c6f4eb unverified no licence file found · pointer only
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models 1 Nov 2024 JayZhang42/SLED/utils/utils_gsm8k.py d4bd3ab60e7a743a unverified no licence file found · pointer only
TidalDecode: Fast and Accurate LLM Decoding with Position Persistent Sparse Attention 7 Oct 2024 DerrickYLJ/TidalDecode/src/utils.py d196dde52e17237c ran Apache-2.0 (permissive)
Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting 27 Sep 2024 multihuntr/gff/gff/data_sources.py 223d3628a64c7b3c unverified CC0-1.0 (permissive)
Subspace Prototype Guidance for Mitigating Class Imbalance in Point Cloud Semantic Segmentation 20 Aug 2024 Javion11/PointLiBR/openpoints/dataset/data_util.py 556e417290a6e1fd unverified MIT (permissive)
SirLLM: Streaming Infinite Retentive LLM 21 May 2024 zoeyyao27/sirllm/sir_llm/utils.py d196dde52e17237c ran no licence file found · pointer only
X-3D: Explicit 3D Structure Modeling for Point Cloud Recognition 23 Apr 2024 sunshuofeng/X-3D/openpoints/dataset/data_util.py 556e417290a6e1fd unverified MIT (permissive)
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation 3 Mar 2024 identical code first harvested elsewhere 0f14b819bc361c25 unverified licence of this copy not recorded
Point Cloud Mamba: Point Cloud Learning via State Space Model 1 Mar 2024 skyworkai/pointcloudmamba/openpoints/dataset/data_util.py 556e417290a6e1fd unverified no licence file found · pointer only
SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully 11 Jan 2024 0-kaikai-0/sh2/factor_eval.py 0f14b819bc361c25 unverified no licence file found · pointer only
Alleviating Hallucinations of Large Language Models through Induced Hallucinations 25 Dec 2023 hillzhang1999/icd/src/benchmark_evaluation/factscore_eval.py f4c68c4850723e81 unverified MIT (permissive)
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models 7 Sep 2023 voidism/DoLa/factor_eval.py 0f14b819bc361c25 unverified no licence file found · pointer only
Coarse-to-Fine: Learning Compact Discriminative Representation for Single-Stage Image Retrieval 8 Aug 2023 bassyess/CFCD/core/io.py e10bd0e3f25f2b57 unverified MIT (permissive)
Self-positioning Point-based Transformer for Point Cloud Understanding 29 Mar 2023 mlvlab/SPoTr/openpoints/dataset/data_util.py 556e417290a6e1fd unverified MIT (permissive)
Algorithm Selection for Deep Active Learning with Imbalanced Datasets 14 Feb 2023 jifanz/tailor/dataset/imagenet_dataset.py fd2ed15a69e5dcfe unverified MIT (permissive)
PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds 30 Jul 2022 xiaoaoran/polarmix/model_zoo.py 82545d97082ff5f4 unverified MIT (permissive)
PointVector: A Vector Representation In Point Cloud Analysis 21 May 2022 guochengqian/openpoints/dataset/data_util.py 556e417290a6e1fd unverified MIT (permissive)
Generalizing Few-Shot NAS with Gradient Matching 29 Mar 2022 skhu101/GM-NAS/Proxylessnas-GM/proxyless_nas/utils.py ecbe897d347181d9 unverified MIT (permissive)
Datasets for Studying Generalization from Easy to Hard Examples 13 Aug 2021 aks2203/easy-to-hard-data/easy_to_hard_data.py da38ca7f90f7a02c unverified MIT (permissive)
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features 6 Aug 2021 feymanpriv/DOLG/core/io.py e10bd0e3f25f2b57 unverified MIT (permissive)
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise 21 Jun 2021 hongxin001/ODNL/algorithms/odnl.py 0105f183fe8b9666 unverified no licence file found · pointer only
Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions 27 Oct 2020 cmougan/WRI_WellBeing_Data_Layer/dssg/dataio/ntl_data_extraction.py d234e70ea0c97ce9 unverified MIT (permissive)
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution 31 Jul 2020 mit-han-lab/spvnas/model_zoo.py 82545d97082ff5f4 unverified MIT (permissive)
Once-for-All: Train One Network and Specialize it for Efficient Deployment 26 Aug 2019 seulkiyeom/once-for-all/utils.py 3396d2fc2ff97e58 unverified Apache-2.0 (permissive)
On Network Design Spaces for Visual Recognition 30 May 2019 feymanpriv/pymetric/metric/core/io.py e10bd0e3f25f2b57 unverified MIT recorded; this copy not marked cleared · pointer only
Provably Powerful Graph Networks 27 May 2019 hadarser/ProvablyPowerfulGraphNetworks/utils/get_data.py 7838e53265948514 unverified Apache-2.0 (permissive)
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware 2 Dec 2018 MIT-HAN-LAB/ProxylessNAS/proxyless_nas/utils.py ecbe897d347181d9 unverified MIT (permissive)
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware 2 Dec 2018 AhmadQasim/proxylessnas-dense/proxyless_nas/utils.py fc80172ec891659e unverified Apache-2.0 (permissive)
arXiv:openreview_trSWJ99WzS DerrickYLJ/LessIsMore/src/utils.py d196dde52e17237c ran Apache-2.0 (permissive)
arXiv:Lin_Meta_Architecture_for_Point_Cloud_Analysis_CVPR_2023_paper linhaojia13/PointMetaBase/openpoints/dataset/data_util.py 556e417290a6e1fd 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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