Home › Code › nll_loss

nll_loss

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

nll_loss appears in the code Syntology harvested for 29 papers, as 20 distinct code bodies found in 29 places (a place is one code body under one paper). At least one of them ran in 10 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 nll_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 9 of the 20 distinct code bodies named nll_loss; 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
2ran · fixture could not drive it
5ran
11unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 10 of the 29 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

29 papers shown of 29, newest first; 29 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; 3 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
Enabling Progressive Whole-slide Image Analysis with Multi-scale Pyramidal Network added by Syntology 2026-02 (from id) szc19990412/TransMIL/MyLoss/ND_Crossentropy.py 2f6a7a4faec6cb11 unverified no licence file found · pointer only
OTSurv: A Novel Multiple Instance Learning Framework for Survival Prediction with Heterogeneity-aware Optimal Transport 25 Jun 2025 y-research-sbu/otsurv/src/utils/losses.py 15821d5a95c321e7 unverified no licence file found · pointer only
Revisiting End-to-End Learning with Slide-level Supervision in Computational Pathology 3 Jun 2025 dearcaat/e2e-wsi-abmilx/train_utils.py 634cc658cc2e7e43 ran · fixture could not drive it no licence file found · pointer only
Second-Order Forward-Mode Automatic Differentiation for Optimization 19 Aug 2024 sri-csl/fomoh/src/fomoh/nn.py f3958881d36885b5 ran BSD-2-Clause (permissive)
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model 22 Jul 2024 cassie07/pathomics/PathOmics/model_and_training_utils/Customized_Loss.py 62ede8fe77ab4913 ran · fixture could not drive it no licence file found · pointer only
Multimodal Prototyping for cancer survival prediction 28 Jun 2024 mahmoodlab/MMP/src/mil_models/model_multimodal.py 15821d5a95c321e7 unverified licence not identified · pointer only
CausalFormer: An Interpretable Transformer for Temporal Causal Discovery 24 Jun 2024 lingbai-kong/causalformer/model/loss.py d1be63c8c9a37d8b ran GPL-3.0 (copyleft) · pointer only
Cohort-Individual Cooperative Learning for Multimodal Cancer Survival Analysis 3 Apr 2024 moothes/ccl-survival/utils/loss_factory.py 6da69690929061c7 ran no licence file found · pointer only
MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology 11 Mar 2024 isyangshu/mambamil/utils/survival_loss.py 7acefd0931bba0fe ran no licence file found · pointer only
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling 29 Feb 2024 rose-stl-lab/mfrnp/model/loss.py 1876fb7ce633ef5f ran MIT (permissive)
HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data 15 Nov 2023 konst-int-i/mm-lego/mm_lego/models/losses.py 8109ef4e167f0ad9 unverified Apache-2.0 (permissive)
Multimodal Optimal Transport-based Co-Attention Transformer with Global Structure Consistency for Survival Prediction 14 Jun 2023 JJ-ZHOU-Code/RobustMultiModel/models/model_coattn.py 62ede8fe77ab4913 ran · fixture could not drive it no licence file found · pointer only
A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension 5 May 2023 callsys/textvr/model/loss.py 8c2db3d4435816c0 unverified MIT (permissive)
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees 6 Jun 2022 VirtuosoResearch/Robust-fine-tuning/exps_on_image_datasets/model/loss.py 8c2db3d4435816c0 unverified MIT (permissive)
Guidelines and Evaluation of Clinical Explainable AI in Medical Image Analysis 16 Feb 2022 weinajin/multimodal_explanation/code/model/loss.py 8c2db3d4435816c0 unverified MIT (permissive)
ReasonBERT: Pre-trained to Reason with Distant Supervision 10 Sep 2021 sunlab-osu/reasonbert/model/loss.py 8c2db3d4435816c0 unverified Apache-2.0 (permissive)
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval 1 Apr 2021 m-bain/frozen-in-time/model/loss.py 8c2db3d4435816c0 unverified MIT (permissive)
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates 24 Aug 2020 Lingkai-Kong/SDE-Net/YearMSD/SDE_regression.py 90e12c93d2ca890b ran · honoured contract fingerprinted Apache-2.0 (permissive)
Telescoping Density-Ratio Estimation 22 Jun 2020 benrhodes26/tre_code/representation_learning_evaluation.py bc6b7cfb69c9976e unverified MIT (permissive)
Gaussianization Flows 4 Mar 2020 IPL-UV/rbig_jax/rbig_jax/stopping.py 36a600d9e04a706d unverified MIT (permissive)
Paraphrase Generation with Latent Bag of Words 7 Jan 2020 FranxYao/dgm_latent_bow/src/bow_seq2seq.py 9a8e1721a125fdd2 unverified MIT (permissive)
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference 30 Aug 2019 tpospisi/DeepCDE/deepcde/deepcde_tensorflow.py e952a89a011eab1e unverified MIT (permissive)
TAPER: Time-Aware Patient EHR Representation 11 Aug 2019 sajaddarabi/TAPER/model/loss.py 8ee89582184d0fd2 unverified MIT (permissive)
Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks 15 May 2019 tae898/age-gender/model/loss.py f733c7f26bd8c1dc unverified Apache-2.0 (permissive)
Structured Inference Networks for Nonlinear State Space Models 30 Sep 2016 yjlolo/pytorch-deep-markov-model/model/loss.py b5351f56bbfd3e22 unverified MIT (permissive)
Recurrent Neural Network Regularization 8 Sep 2014 Goodideax/lstm-negtive/ensemble.py dd2e42e616936d7a ran · our draft was wrong no licence file found · pointer only
arXiv:2023.emnlp-main.979 cyclexu/TacoPrompt/TacoPrompt/model/loss.py 8c2db3d4435816c0 unverified MIT (permissive)
arXiv:2022.findings-emnlp.24 StanLei52/TQVSR/models/loss.py 8c2db3d4435816c0 unverified MIT (permissive)
arXiv:2022.findings-acl.116 vistec-AI/Thai-NNER/model/loss.py 8c2db3d4435816c0 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