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make_table

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

make_table appears in the code Syntology harvested for 15 papers, as 9 distinct code bodies found in 18 places (a place is one code body under one paper). At least one of them ran in 1 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 make_table 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 9 distinct code bodies named make_table; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
0ran
8unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 18 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

15 papers shown of 15, newest first; 18 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
AlphaQ: Calibration-Free Bit Allocation for Mixture-of-Experts Quantization added by Syntology 2026-06 (from id) Superone77/AlphaQ/eval_utils.py f5f924ce5962ca8f unverified no licence file found · pointer only
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora 10 Apr 2025 babylm/evaluation-pipeline/lm_eval/evaluator.py 910a58b3f0fe9967 unverified MIT (permissive)
Sirius: Contextual Sparsity with Correction for Efficient LLMs 5 Sep 2024 identical code first harvested elsewhere 9d95c14130837ee4 unverified licence of this copy not recorded
Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation 1 Apr 2024 hdong920/griffin/src/lm_eval/evaluator.py 9d95c14130837ee4 unverified no licence file found · pointer only
A Comprehensive Evaluation of Quantization Strategies for Large Language Models 26 Feb 2024 cordercorder/quant_eval/quant/SpQR/lm-evaluation-harness/lm_eval/evaluator.py 9d95c14130837ee4 unverified no licence file found · pointer only
FinBen: A Holistic Financial Benchmark for Large Language Models 20 Feb 2024 chancefocus/pixiu/src/evaluator.py 9d95c14130837ee4 unverified MIT (permissive)
QuRating: Selecting High-Quality Data for Training Language Models 15 Feb 2024 princeton-nlp/QuRating/eval/lm-evaluation-harness/lm_eval/evaluator.py 9d95c14130837ee4 unverified no licence file found · pointer only
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference 14 Feb 2024 hdong920/less/src/lm_eval/evaluator.py 9d95c14130837ee4 unverified no licence file found · pointer only
LAiW: A Chinese Legal Large Language Models Benchmark 9 Oct 2023 dai-shen/laiw/src/evaluator.py 9d95c14130837ee4 unverified MIT (permissive)
Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback 29 Jul 2023 nlp-uoregon/mlmm-evaluation/lm_eval/evaluator.py 9d95c14130837ee4 unverified Apache-2.0 (permissive)
Do prompt positions really matter? 23 May 2023 milliemaoo/prompt-position/lm_eval/evaluator.py 9d95c14130837ee4 unverified MIT (permissive)
Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams 29 Mar 2023 piresramon/gpt-4-enem/lm_eval/evaluator.py 9d95c14130837ee4 unverified MIT (permissive)
Uncertainty Sets for Image Classifiers using Conformal Prediction 29 Sep 2020 aangelopoulos/conformal_classification/experiments/table1.py 8ce51944e3958c60 unverified MIT (permissive)
Uncertainty Sets for Image Classifiers using Conformal Prediction 29 Sep 2020 aangelopoulos/conformal_classification/experiments/table11.py 837d496b65e5409a unverified MIT (permissive)
Uncertainty Sets for Image Classifiers using Conformal Prediction 29 Sep 2020 aangelopoulos/conformal_classification/experiments/table2.py 3e5323ecb83f4191 unverified MIT (permissive)
Uncertainty Sets for Image Classifiers using Conformal Prediction 29 Sep 2020 aangelopoulos/conformal_classification/experiments/table5.py 153f3eb42aa57f6e unverified MIT (permissive)
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior? 4 May 2020 peterbhase/InterpretableNLP-ACL2020/tabular/anchor/make_graphs_and_table.py 1db3f658ae6ec3e0 unverified MIT (permissive)
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages 16 Mar 2020 rasoolims/stanza/stanza/pipeline/core.py 99a85098b6a5141d ran · our draft was wrong licence not identified · 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