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entropy_loss

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

entropy_loss appears in the code Syntology harvested for 42 papers, as 21 distinct code bodies found in 42 places (a place is one code body under one paper). At least one of them ran in 22 of the papers; 12 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 entropy_loss 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 12 of the 21 distinct code bodies named entropy_loss; 9 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
1ran · violated contract
4ran · our draft was wrong
1ran · fixture could not drive it
5ran
9unverified
12fingerprinted

Licence is a property of each copy, so it is counted per place: 15 of the 42 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

42 papers shown of 42, newest first; 42 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; 5 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
StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs added by Syntology 2025-09 (from id) Tencent/StableToken/src/model/voting_lfq.py 768a1c2f20b2bc72 unverified licence not identified · pointer only
RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning 17 Dec 2024 KanghoonYoon/torch-rasgg/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified no licence file found · pointer only
LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior 28 Oct 2024 hywang66/LARP/models/bottleneck.py b4701e8bb46ce4c9 unverified MIT (permissive)
PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation 8 Sep 2024 axi404/pmt/code/utils/losses.py f8c429b95e4ae707 ran fingerprinted no licence file found · pointer only
Enhancing Domain Adaptation through Prompt Gradient Alignment 13 Jun 2024 viethoang1512/pga/LA/main_uda.py bf4375591fccddac ran · our draft was wrong fingerprinted no licence file found · pointer only
Leveraging Predicate and Triplet Learning for Scene Graph Generation 4 Jun 2024 jkli1998/drm/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT (permissive)
AtomGS: Atomizing Gaussian Splatting for High-Fidelity Radiance Field 20 May 2024 RongLiu-Leo/AtomGS/utils/loss_utils.py eef6a1a818e3089f ran fingerprinted licence not identified · pointer only
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost 9 May 2024 ethanygao/aux-nas/networks/stagewise_search_aux.py b2ce8e695ddf3a7c ran · honoured contract fingerprinted no licence file found · pointer only
Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation 13 Apr 2024 MQinghe/MiDSS/code/utils/losses.py f8c429b95e4ae707 ran fingerprinted Apache-2.0 (permissive)
Decomposition-based Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation 6 Apr 2024 sstary/ssrs/GLGAN/loss.py 360b5a2923d789bd ran fingerprinted Apache-2.0 (permissive)
Adaptive Self-training Framework for Fine-grained Scene Graph Generation 18 Jan 2024 rlqja1107/torch-ST-SGG/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified no licence file found · pointer only
Combating Bilateral Edge Noise for Robust Link Prediction 2 Nov 2023 SJYuCNEL/PRI-Graphs/graph_sparse.py ebac4362ac395e38 unverified no licence file found · pointer only
SUMMIT: Source-Free Adaptation of Uni-Modal Models to Multi-Modal Targets 23 Aug 2023 csimo005/SUMMIT/xmuda/models/losses.py 6096bcdf058e4f0f ran fingerprinted licence not identified · pointer only
Vision Relation Transformer for Unbiased Scene Graph Generation 18 Aug 2023 visinf/veto/pysgg/layers/entropy_loss.py 2d943c0c96e61f16 unverified Apache-2.0 (permissive)
Compositional Feature Augmentation for Unbiased Scene Graph Generation 13 Aug 2023 hkust-longgroup/cfa/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT (permissive)
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection 6 Aug 2023 xcyao00/fod/losses.py d6ada2dc4e5d3719 ran fingerprinted MIT (permissive)
Prototype-based Embedding Network for Scene Graph Generation 13 Mar 2023 VL-Group/PENET/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT recorded; this copy not marked cleared · pointer only
Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions 21 Jul 2022 theo2021/OnDA/framework/domain_adaptation/methods/prototypes.py d26c4d52f259e495 ran · fixture could not drive it fingerprinted GPL-2.0 (copyleft) · pointer only
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning 15 May 2022 microsoft/semi-supervised-learning/semilearn/algorithms/freematch/freematch.py e4d38b3bf55a8430 ran · our draft was wrong fingerprinted MIT (permissive)
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference 15 Apr 2022 hushell/pmf_cvpr22/models/deploy.py af188f96f841e377 unverified Apache-2.0 (permissive)
Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation 18 Mar 2022 dongxingning/SHA-GCL-for-SGG/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT recorded; this copy not marked cleared · pointer only
Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation 18 Jan 2022 ChCh1999/RTPB/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT (permissive)
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank 27 Apr 2021 Shathe/SemiSeg-Contrastive/trainSSL.py c5fce4bac70be375 unverified Apache-2.0 (permissive)
Visual Distant Supervision for Scene Graph Generation 29 Mar 2021 thunlp/VisualDS/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT (permissive)
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness 15 Oct 2020 garyzhao/ME-ADA/model_cifar.py 10487302bd997fba ran · our draft was wrong fingerprinted BSD-3-Clause (permissive)
Geometry-aware Instance-reweighted Adversarial Training 5 Oct 2020 zjfheart/Geometry-aware-Instance-reweighted-Adversarial-Training/GAIR_RST/losses.py 044ec38c1bb631ec ran · our draft was wrong fingerprinted no licence file found · pointer only
Semi-supervised Medical Image Segmentation through Dual-task Consistency 9 Sep 2020 HiLab-git/DTC/code/utils/losses.py f8c429b95e4ae707 ran fingerprinted MIT (permissive)
Learning to Generate Noise for Multi-Attack Robustness 22 Jun 2020 divyam3897/MNG_AC/losses.py 044ec38c1bb631ec ran · our draft was wrong fingerprinted MIT (permissive)
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition 21 Apr 2020 MRLoghmani/relative-rotation/code/utils.py 2b7cf311ed8497dd unverified MIT (permissive)
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision 16 Apr 2020 feipanir/intrada/ADVENT/advent/utils/loss.py 360b5a2923d789bd ran fingerprinted MIT (permissive)
Semi-Supervised Semantic Segmentation with Cross-Consistency Training 19 Mar 2020 Luoxd1996/DTC/code/utils/losses.py f8c429b95e4ae707 ran fingerprinted MIT (permissive)
Unbiased Scene Graph Generation from Biased Training 27 Feb 2020 KaihuaTang/Scene-Graph-Benchmark.pytorch/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT recorded; this copy not marked cleared · pointer only
Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation 16 Jul 2019 bx0903/pdc/code/utils/losses.py f8c429b95e4ae707 ran fingerprinted MIT (permissive)
Adversarial Lipschitz Regularization 12 Jul 2019 dterjek/adversarial_lipschitz_regularization/semisup.py 052b8a5f1861248f ran · violated contract fingerprinted no licence file found · pointer only
Unlabeled Data Improves Adversarial Robustness 31 May 2019 yguooo/semisup-adv/losses.py 044ec38c1bb631ec ran · our draft was wrong fingerprinted MIT (permissive)
Reconstruction Network for Video Captioning 30 Mar 2018 hobincar/RecNet/losses.py 21b15c9b43e9b7a2 unverified MIT (permissive)
Describing Videos by Exploiting Temporal Structure 27 Feb 2015 hobincar/SA-LSTM/losses.py 21b15c9b43e9b7a2 unverified MIT (permissive)
arXiv:openreview_WkPYWGHQR2 arakotom/flowllp/bagloss.py 01933e9683b7dcf8 unverified MIT (permissive)
arXiv:aaai_25356 wanglei0618/A-PFG/maskrcnn_benchmark/layers/entropy_loss.py 2d943c0c96e61f16 unverified MIT (permissive)
arXiv:Zhou_XNet_Wavelet-Based_Low_and_High_Frequency_Fusion_Networks_for_Fully-_ICCV_2023_paper Yanfeng-Zhou/XNet/loss/loss_function.py f8c429b95e4ae707 ran fingerprinted MIT (permissive)
arXiv:Wang_MCF_Mutual_Correction_Framework_for_Semi-Supervised_Medical_Image_Segmentation_CVPR_2023_paper WYC-321/MCF/code/utils/losses.py f8c429b95e4ae707 ran fingerprinted MIT (permissive)
arXiv:Miao_CauSSL_Causality-inspired_Semi-supervised_Learning_for_Medical_Image_Segmentation_ICCV_2023_paper JuzhengMiao/CauSSL/utils/losses.py f8c429b95e4ae707 ran fingerprinted 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".

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