Home › Code › compute_cost

compute_cost

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

compute_cost appears in the code Syntology harvested for 14 papers, as 14 distinct code bodies found in 14 places (a place is one code body under one paper). At least one of them ran in 3 of the papers; 1 of the code bodies carries 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 compute_cost 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 14 distinct code bodies named compute_cost; 11 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
1ran · fixture could not drive it
0ran
11unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 2 of the 14 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

14 papers shown of 14, newest first; 14 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 1 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
DataParasite Enables Scalable and Repurposable Online Data Curation added by Syntology 2026-01 (from id) mengysun/DataParasite/src/data_parasite.py 645666446aafcbfe ran · honoured contract BSD-3-Clause (permissive)
Detecting Harmful Memes with Decoupled Understanding and Guided CoT Reasoning 10 Jun 2025 panFJCharlotte98/HMC/call_gpt.py c46b835f604591c0 unverified MIT (permissive)
Are LLMs Good Zero-Shot Fallacy Classifiers? 19 Oct 2024 panfjcharlotte98/fallacy_detection/models/gpt_based.py b88a86c99705decd unverified MIT (permissive)
Sparse Rewards Can Self-Train Dialogue Agents 6 Sep 2024 asappresearch/josh-llm-simulation-training/josh_train/utils.py 6d3738cda068547c unverified MIT (permissive)
CoverUp: Effective High Coverage Test Generation for Python 24 Mar 2024 plasma-umass/coverup/src/coverup/llm.py def8599068e3dbf6 unverified Apache-2.0 (permissive)
Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation 19 Feb 2024 scailab/paser/src/pretrain_rl.py 3317f307bb2e7fc6 ran · our draft was wrong no licence file found · pointer only
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance 9 May 2023 stanford-futuredata/frugalgpt/src/service/utils.py 5141b572dad4bddf unverified Apache-2.0 (permissive)
Pairwise Fairness for Ordinal Regression 7 May 2021 amazon-research/fair-ordinal-regression/learn_fair_threshold_model/evaluation.py 77331f760d7f305b unverified Apache-2.0 (permissive)
Hybrid Federated Learning: Algorithms and Implementation 22 Dec 2020 564612540/Hybrid-Federated-Learning/model_matching/model_matching.py 8dd003cffc884698 unverified no licence file found · pointer only
Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function 22 Jul 2020 hybridrobotics/car-racing/car_racing/control/lmpc_helper.py 9a70375264b211c3 unverified MIT (permissive)
Federated Learning with Matched Averaging 15 Feb 2020 IBM/FedMA/matching/pfnm.py 0deab229a7b7de8e unverified MIT (permissive)
Statistical Model Aggregation via Parameter Matching 1 Nov 2019 IBM/SPAHM/topicmodeling/matching/gaus_marginal_matching.py 79a0729a8d3b82bb ran · fixture could not drive it fingerprinted MIT (permissive)
Quantum Wasserstein Generative Adversarial Networks 31 Oct 2019 yiminghwang/qWGAN/model/model_hs.py b8bd853d4c85ec09 unverified MIT (permissive)
Bayesian Nonparametric Federated Learning of Neural Networks 28 May 2019 IBM/probabilistic-federated-neural-matching/matching/pfnm.py beed9270a5b69d7a 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".

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