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compute_entropy

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

compute_entropy appears in the code Syntology harvested for 19 papers, as 19 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; 8 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 compute_entropy 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 10 of the 19 distinct code bodies named compute_entropy; 9 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

2ran · honoured contract
0ran · violated contract
3ran · our draft was wrong
2ran · fixture could not drive it
3ran
9unverified
8fingerprinted

Licence is a property of each copy, so it is counted per place: 7 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 4 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
The Dialect Tax: Dialectal Biases Persist throughout the Language Modeling Pipeline added by Syntology 2026-08 (from id) socialnlp/dialecttax/src/dialecttax/logits.py 80bd1696a29c9b2f ran fingerprinted MIT (permissive)
RETLLM: Training and Data-Free MLLMs for Multimodal Information Retrieval added by Syntology 2026-02 (from id) alivecat05/RETLLM/Codes/Qwen_vl.py c98c3c7150fdcd2f unverified Apache-2.0 (permissive)
VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation added by Syntology 2026-02 (from id) deeplearning-wisc/vauq/vauq/scoring.py d1f6db28a2a7ff6a ran · our draft was wrong Apache-2.0 (permissive)
Towards Generalisable Imitation Learning Through Conditioned Transition Estimation and Online Behaviour Alignment added by Syntology 2026-01 (from id) NathanGavenski/UfO/utils/utils.py 58f18a79a5425d3a unverified no licence file found · pointer only
What Happens During the Loss Plateau? Understanding Abrupt Learning in Transformers 16 Jun 2025 pulkitgopalani/tf-loss-plateau/src/train_add.py df1baca5141c4e64 unverified no licence file found · pointer only
HippoMM: Hippocampal-inspired Multimodal Memory for Long Audiovisual Event Understanding 2025-04 (from id) linyueqian/hippomm/hippomm/utils/vector_ops.py 726aa68ab9de3ced unverified MIT (permissive)
On the Generalization of Representation Uncertainty in Earth Observation 10 Mar 2025 Orion-AI-Lab/EOUncertaintyGeneralization/inference/infere_uncertainties.py d20673febf1cc6cb unverified MIT (permissive)
Intersectional Unfairness Discovery 31 May 2024 xugezheng/bggn/engine/engine_vae_bias.py 42b500b9cf00fc46 ran · fixture could not drive it fingerprinted no licence file found · pointer only
Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models 17 Apr 2024 Yue-LLM-Pit/SCoP/utils.py ef37703ecc5c8527 ran fingerprinted MIT (permissive)
Distinguishing the Knowable from the Unknowable with Language Models 5 Feb 2024 gahdritz/llm_uncertainty/repetition.py 625d925ef1efd4f4 ran fingerprinted Apache-2.0 (permissive)
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling 15 Nov 2023 ucsb-nlp-chang/llm_uncertainty/evaluate_uq_qa.py 20cdfa5f66a261c8 ran · honoured contract fingerprinted no licence file found · pointer only
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset 9 Sep 2023 bramiozo/PubScience/src/pubscience/clean/cleaner.py 849de0c8feb5a9d5 unverified Apache-2.0 (permissive)
Rethinking Data-Free Quantization as a Zero-Sum Game 19 Feb 2023 hfutqian/AdaSG/AdaSG_code/CIFAR/trainer.py 90726473320040cd ran · our draft was wrong fingerprinted Apache-2.0 (permissive)
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model 14 Dec 2022 maohaos2/PosthocUQ/metrics.py ecf2ba21313d2f00 unverified MIT (permissive)
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation 7 Sep 2022 zanchangtong/ptvsri/analysis/lpd.py 6e072a02b03fd090 unverified MIT (permissive)
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain 20 Jul 2022 boschresearch/sourcegen/sourcegen/models/sourcegen/models.py 3a05a13349f6cd51 ran · fixture could not drive it fingerprinted AGPL-3.0 (copyleft) · pointer only
Variational Model Inversion Attacks 26 Jan 2022 wangkua1/vmi/evaluate_samples.py 44f8073d78252a7a ran · our draft was wrong fingerprinted no licence file found · pointer only
Dynamic Convolution: Attention over Convolution Kernels 7 Dec 2019 TArdelean/DynamicConvolution/inspect_attention.py e36ca5f4167e4e43 unverified MIT (permissive)
Entropy and mutual information in models of deep neural networks 24 May 2018 sphinxteam/dnner/dnner/compute_entropy.py 2df4bae2b5006e05 ran · honoured contract 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".

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