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ce_loss

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

ce_loss appears in the code Syntology harvested for 34 papers, as 33 distinct code bodies found in 36 places (a place is one code body under one paper). At least one of them ran in 21 of the papers; 6 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 ce_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 20 of the 33 distinct code bodies named ce_loss; 13 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
9ran · fixture could not drive it
6ran
13unverified
6fingerprinted

Licence is a property of each copy, so it is counted per place: 9 of the 36 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

34 papers shown of 34, newest first; 36 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 2 papers added by Syntology; 4 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
Orthogonal Representation Editing: Decoupling Semantic Entanglement in Batch Knowledge Editing of LLMs added by Syntology 2026-06 (from id) YVVH/ORE/ORE/ORE_main.py 14374bd37af63bc3 ran MIT (permissive)
Keep It on a Leash: Controllable Pseudo-label Generation Towards Realistic Long-Tailed Semi-Supervised Learning added by Syntology 2025-10 (from id) yaxinhou/CPG/semilearn/core/criterions/cross_entropy.py 6554d2f5118ba705 unverified no licence file found · pointer only
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes 26 Jun 2025 yifanycc/sharpzo/clip/bb_clip_model.py 199d6f35dcbfe379 ran · our draft was wrong fingerprinted MIT (permissive)
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes 26 Jun 2025 yifanycc/sharpzo/main_sharpzo.py 3d3bb1e71ff2f61e unverified MIT (permissive)
arXiv:2503.02231 2025-03 (from id) BoCheng-96/CGMatch/semilearn/core/criterions/cross_entropy.py 6554d2f5118ba705 unverified MIT (permissive)
Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding 14 Feb 2025 ltluttmann/marl4msprp/marlprp/algorithms/losses.py 2e769f511bdda9c4 unverified MIT (permissive)
(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning 30 Oct 2024 seungjoo-ai/FLFL-NeurIPS24/src/algorithm/flfl.py ac50b71552df6ea1 ran · fixture could not drive it MIT (permissive)
Large-Scale 3D Medical Image Pre-training with Geometric Context Priors 13 Oct 2024 luffy03/large-scale-medical/Omni-supervised/models/voco_head.py eb30e78d89562dd2 ran fingerprinted Apache-2.0 (permissive)
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model 22 Jul 2024 cassie07/pathomics/PathOmics/model_and_training_utils/Customized_Loss.py e733788b8a808833 ran no licence file found · pointer only
VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis 27 Feb 2024 Luffy03/VoCo/models/voco_head.py a99b36c20266880b ran · honoured contract fingerprinted Apache-2.0 (permissive)
Robust Training of Federated Models with Extremely Label Deficiency 22 Feb 2024 visitworld123/Twin-sight/trainers/normal_trainer.py 5623e1ae3f61cea9 unverified MIT (permissive)
Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models 6 Feb 2024 mrflogs/craft/main_craft.py 199d6f35dcbfe379 ran · our draft was wrong fingerprinted MIT (permissive)
Repeat After Me: Transformers are Better than State Space Models at Copying 1 Feb 2024 sjelassi/transformers_ssm_copy/synthetic_exps/train_utils.py b9b929da44e45018 ran MIT (permissive)
Putting the Object Back into Video Object Segmentation 19 Oct 2023 hkchengrex/Cutie/cutie/model/losses.py 066adf2df6def74d ran MIT (permissive)
Distributionally Robust Post-hoc Classifiers under Prior Shifts 16 Sep 2023 weijiaheng/drops/drops_test_time.py a85f3df5207d6bdf unverified no licence file found · pointer only
Auto-Regressive Next-Token Predictors are Universal Learners 13 Sep 2023 emalach/linearlm/training/linear_decoder.py 1cd9d3020ea9cf57 ran · fixture could not drive it no licence file found · pointer only
Enhancing Sample Utilization through Sample Adaptive Augmentation in Semi-Supervised Learning 7 Sep 2023 GuanGui-nju/SAA/models/fixmatch/dafree.py f31099eaf0227660 ran · fixture could not drive it no licence file found · pointer only
IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization 25 Aug 2023 nukezil/IOMatch/semilearn/algorithms/utils/loss.py c2e202cd61888d8e ran fingerprinted MIT (permissive)
Reliable Federated Disentangling Network for Non-IID Domain Feature 30 Jan 2023 looking9218/rfeddis/federated/RFedDis_Domainnet.py c6bf27cd6b8c13be ran · our draft was wrong no licence file found · pointer only
SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning 26 Jan 2023 torchssl/torchssl/models/softmatch/softmatch.py ceaa5f15ab49feba ran · fixture could not drive it MIT (permissive)
Teach-DETR: Better Training DETR with Teachers 22 Nov 2022 leonhlj/teach-detr/H-Deformable-DETR/models/deformable_detr.py ddb9b0f4a2035653 unverified MIT (permissive)
RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning 9 Aug 2022 NJUyued/RDA4RobustSSL/models/rda/rda.py 0c1d927c0e848f5c ran · fixture could not drive it MIT (permissive)
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning 15 Apr 2022 HazyResearch/thanos-code/unagi/tasks/loss_modules.py 4251f968142da139 unverified Apache-2.0 (permissive)
Better Supervisory Signals by Observing Learning Paths 4 Mar 2022 joshua-ren/better_supervisory_signal/utils.py 21fe6fa61f6e0652 ran · honoured contract fingerprinted MIT (permissive)
Guidelines and Evaluation of Clinical Explainable AI in Medical Image Analysis 16 Feb 2022 weinajin/multimodal_explanation/code/model/loss.py bda86860758146a3 unverified MIT (permissive)
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling 15 Oct 2021 beandkay/sequencematch/models/flexmatch/flexmatch.py 1b2ef05b7424074f ran · fixture could not drive it MIT (permissive)
Semi-Supervised Learning with Multi-Head Co-Training 10 Jul 2021 chenmc1996/Multi-Head-Co-Training/multi_head.py 89e54e0adff22983 ran · fixture could not drive it no licence file found · pointer only
Trusted Multi-View Classification 3 Feb 2021 hanmenghan/TMC/TMC ICLR/model.py 0457de81106bb225 ran · our draft was wrong no licence file found · pointer only
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence 21 Jan 2020 gomezzz/MSMatch/models/fixmatch/fixmatch.py 9723f46ec1689a37 ran · fixture could not drive it MIT (permissive)
Corners for Layout: End-to-End Layout Recovery from 360 Images 19 Mar 2019 palver7/CFLPytorch/train_CFL.py 64b75e2a61be6d29 ran · fixture could not drive it fingerprinted no licence file found · pointer only
A Probabilistic U-Net for Segmentation of Ambiguous Images 13 Jun 2018 MIC-DKFZ/probabilistic_unet/utils/training_utils.py 1154f612e91c9287 unverified Apache-2.0 (permissive)
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning 14 Nov 2017 SenWu/emmental-tutorials/chexnet/task.py 463d3f2f4d6be38d unverified MIT (permissive)
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning 14 Nov 2017 SenWu/emmental-tutorials/glue/glue_tasks.py 188aff3170045ab9 unverified MIT (permissive)
arXiv:ijcai2024_0712 nyh-a/CoSTC/model/loss.py bda86860758146a3 unverified MIT (permissive)
arXiv:aaai_25883 alcorreia/cm-tpm/utils/losses.py fbb033fb1cd79f44 unverified MIT (permissive)
arXiv:136810034 Sense-X/UniNet/losses.py 71964fb5d0fe8809 unverified 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".

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