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percentile

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

percentile appears in the code Syntology harvested for 12 papers, as 9 distinct code bodies found in 12 places (a place is one code body under one paper). At least one of them ran in 8 of the papers; 3 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 percentile 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 6 of the 9 distinct code bodies named percentile; 3 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
1ran · fixture could not drive it
2ran
3unverified
3fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 12 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

12 papers shown of 12, newest first; 12 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 3 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
Hardware-Aware FP4 FlashAttention-4 added by Syntology 2026-09 (from id) MrHuff/fp4-fa4/results/fp4_fa4_technical_report_v2_20260819/export_llama8b_b4_snapshot.py 5284c9d8206ffe40 unverified Apache-2.0 (permissive)
TraceLab: Characterizing Coding Agent Workloads for LLM Serving added by Syntology 2026-06 (from id) uw-syfi/TraceLab/artifacts/utils/growth.py f5d51d90d1032ddd ran Apache-2.0 (permissive)
Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts added by Syntology 2025-10 (from id) BaiLibl/ShadowPool/models/resnet_moe.py 3b99baf0c1a4b7f2 unverified no licence file found · pointer only
Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient 11 Oct 2024 realwenlongwang/Drama/agents.py adce9ddcc08da8dc ran fingerprinted no licence file found · pointer only
EventRPG: Event Data Augmentation with Relevance Propagation Guidance 14 Mar 2024 myuansun/eventrpg/utils/RelCAM.py 1b03542f209fada4 ran · fixture could not drive it fingerprinted MIT (permissive)
Continual Learning: Forget-free Winning Subnetworks for Video Representations 19 Dec 2023 ihaeyong/pnr/model/subnet.py 913e2d426938c7d4 ran · our draft was wrong MIT (permissive)
STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning 14 Oct 2023 weipu-zhang/storm/agents.py adce9ddcc08da8dc ran fingerprinted no licence file found · pointer only
Robust Mixture-of-Expert Training for Convolutional Neural Networks 19 Aug 2023 optml-group/robust-moe-cnn/models/resnet_cifar_moe.py 3b99baf0c1a4b7f2 unverified no licence file found · pointer only
On the Soft-Subnetwork for Few-shot Class Incremental Learning 15 Sep 2022 ihaeyong/SoftNet-3DLS/subnet.py 913e2d426938c7d4 ran · our draft was wrong no licence file found · pointer only
DCT-SNN: Using DCT to Distribute Spatial Information over Time for Learning Low-Latency Spiking Neural Networks 5 Oct 2020 SayeedChowdhury/dct-snn/spike_model_cifar.py cc175be6213cc918 ran · our draft was wrong fingerprinted no licence file found · pointer only
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds 5 Aug 2020 vlievin/ovis/ovis/analysis/utils.py 290d2878c24757d5 unverified MIT (permissive)
Adversarial Robustness Guarantees for Random Deep Neural Networks 13 Apr 2020 bkiani/Adversarial-robustness-guarantees-for-random-deep-neural-networks/analyze_csv.py 02e692988a2d9b6c ran · our draft was wrong no licence file found · pointer only

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