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filter_data

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

filter_data appears in the code Syntology harvested for 19 papers, as 13 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 filter_data 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 13 distinct code bodies named filter_data; 9 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
1ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
3ran
9unverified
0fingerprinted

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

19 papers shown of 19, 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, and the graph's for 6 papers added by Syntology; 4 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
Rethinking Multimodal Time-Series Forecasting Evaluation added by Syntology 2026-07 (from id) decisionintelligence/TFB/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran MIT (permissive)
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection added by Syntology 2026-04 (from id) decisionintelligence/TAB/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran no licence file found · pointer only
CoRA: Boosting Time Series Foundation Models for Multivariate Forecasting through Correlation-aware Adapter added by Syntology 2026-03 (from id) decisionintelligence/CoRA/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran no licence file found · pointer only
Enhancing Goal Inference via Correction Timing added by Syntology 2026-02 (from id) iqr-lab/correction-timing/codes/where_model.py 104b7e2ec9e26645 unverified MIT (permissive)
DBLoss: Decomposition-based Loss Function for Time Series Forecasting added by Syntology 2025-10 (from id) decisionintelligence/DBLoss/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran MIT (permissive)
Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection added by Syntology 2025-10 (from id) decisionintelligence/CATCH/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran no licence file found · pointer only
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods 22 Jun 2025 decisionintelligence/tab/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran no licence file found · pointer only
AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms 26 Feb 2025 tsinghua-fib-lab/agentsocietychallenge/data_process.py ff075553db5b65e2 unverified MIT (permissive)
Evaluating the Prompt Steerability of Large Language Models 19 Nov 2024 IBM/prompt-steering/prompt_steerability/persona/benchmark/utils/steering_utils.py f969c3c13217c254 unverified Apache-2.0 (permissive)
Proteus: Preserving Model Confidentiality during Graph Optimizations 18 Apr 2024 proteus-mlsys24/mlsys24-artifact/figures/fig5-gnn-classifier/filter_and_train.py c33bb9497ed9398f ran no licence file found · pointer only
Uncertainty quantification for data-driven weather models 20 Mar 2024 cbuelt/dduq/wb2/ifs.py 8ceaa09f3605111c unverified MIT (permissive)
BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry 28 Jan 2024 samxuxiang/brepgen/dataset.py 69210f5cf001181d ran licence not identified · pointer only
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text 10 Oct 2023 keirp/OpenWebMath/filtering/filter_dataset.py 527338d994af9eda ran · violated contract Apache-2.0 (permissive)
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection 9 Mar 2023 molden/ProbKT/robust_detection/dpl_utils.py d2cb704276043c27 unverified MIT (permissive)
RuleMatrix: Visualizing and Understanding Classifiers with Rules 17 Jul 2018 rulematrix/rule-matrix-py/rulematrix/utils.py a8c4c235c66db7be unverified MIT (permissive)
arXiv:openreview_FYkXNAqq2D decisionintelligence/KITE/ts_benchmark/pipeline.py 005a7fb4e6c758a7 ran MIT (permissive)
arXiv:aaai_16593 SamHaoYuan/DSANForAAAI2021/Preprocess_rr.py 8f069fd78fbb0b80 unverified Apache-2.0 (permissive)
arXiv:2023.findings-emnlp.142 Banner-Z/G-SPEED/wiki_collector/data_processing/prepare.py 2f67a8c3e2ec428d unverified Apache-2.0 (permissive)
arXiv:2021.emnlp-main.635 4AI/TDEER/dataloader.py 8a9742973a1b36b3 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