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prune_linear_layer

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

prune_linear_layer appears in the code Syntology harvested for 40 papers, as 15 distinct code bodies found in 41 places (a place is one code body under one paper). At least one of them ran in 32 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 prune_linear_layer 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 8 of the 15 distinct code bodies named prune_linear_layer; 7 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
6ran · our draft was wrong
0ran · fixture could not drive it
2ran
7unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 11 of the 41 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

40 papers shown of 40, newest first; 41 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; 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
C2A: Client-Customized Adaptation for Parameter-Efficient Federated Learning 1 Nov 2024 yeachan-kr/c2a/transformer_utils.py d12f44df51b174b1 unverified no licence file found · pointer only
Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning 6 Jun 2024 gccnlp/light-peft/peft/src/peft/tuners/lora.py 9d6a7aa341c6be64 ran · our draft was wrong no licence file found · pointer only
Bottleneck-Minimal Indexing for Generative Document Retrieval 12 May 2024 kduxin/Bottleneck-Minimal-Indexing/NCIRetriever/nci_transformers/modeling_utils.py b3504e72ce1153fe ran MIT (permissive)
Text-Guided Molecule Generation with Diffusion Language Model 20 Feb 2024 Deno-V/tgm-dlm/improved-diffusion/improved_diffusion/transformer_model.py 63bf3ad9c297ab92 ran · our draft was wrong no licence file found · pointer only
Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation 19 Dec 2023 lsan2401/rmsin/bert/modeling_utils.py a37615738b3ddcd3 ran no licence file found · pointer only
Mask Grounding for Referring Image Segmentation 19 Dec 2023 yxchng/mask-grounding/bert/modeling_utils.py a37615738b3ddcd3 ran AGPL-3.0 (copyleft) · pointer only
Contrastive Grouping with Transformer for Referring Image Segmentation 2 Sep 2023 toneyaya/cgformer/bert/modeling_utils.py a37615738b3ddcd3 ran MIT (permissive)
Beyond One-to-One: Rethinking the Referring Image Segmentation 26 Aug 2023 toggle1995/RIS-DMMI/bert/modeling_utils.py a37615738b3ddcd3 ran no licence file found · pointer only
When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP 23 May 2023 EdisonNi-hku/MTL4Finance/code/models/modeling_task_embeddings.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models 18 Oct 2022 huggingface/pytorch-transformers/src/transformers/pytorch_utils.py 24ece331635f4b38 unverified Apache-2.0 recorded; this copy not marked cleared · pointer only
Selective Query-guided Debiasing for Video Corpus Moment Retrieval 17 Oct 2022 dbstjswo505/SQuiDNet/model/squidnet.py 409d011257a2b23b ran · our draft was wrong MIT (permissive)
HOP: History-and-Order Aware Pre-training for Vision-and-Language Navigation 22 Mar 2022 yanyuanqiao/hop-vln/tasks/pretrain/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
Alignment Attention by Matching Key and Query Distributions 25 Oct 2021 szhang42/alignment_attention/src/transformers/modeling_albert.py 9d6a7aa341c6be64 ran · our draft was wrong Apache-2.0 (permissive)
SurvTRACE: Transformers for Survival Analysis with Competing Events 2 Oct 2021 RyanWangZf/SurvTRACE/survtrace/modeling_bert.py 5366c196cf596807 unverified MIT (permissive)
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision 24 Aug 2021 FerryHuang/SimVLM/simvlm/modeling_simvlm.py 52de2aaa15da0643 ran · our draft was wrong no licence file found · pointer only
Towards Long-Form Video Understanding 21 Jun 2021 chaoyuaw/lvu/src/models/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark 15 Jun 2021 cbluebenchmark/cblue/cblue/models/zen/modeling.py d30d6c3098df2c42 ran · our draft was wrong Apache-2.0 (permissive)
Plug-and-Blend: A Framework for Controllable Story Generation with Blended Control Codes 23 Mar 2021 xxbidiao/plug-and-blend/gedi_helpers/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
CharBERT: Character-aware Pre-trained Language Model 3 Nov 2020 wtma/CharBERT/modeling/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong Apache-2.0 (permissive)
The elephant in the interpretability room: Why use attention as explanation when we have saliency methods? 12 Oct 2020 jessevig/bertviz/bertviz/transformers_neuron_view/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong Apache-2.0 (permissive)
GeDi: Generative Discriminator Guided Sequence Generation 14 Sep 2020 salesforce/GeDi/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong BSD-3-Clause (permissive)
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech 12 Jul 2020 Pandade1997/tera_asvproof/transformer/model.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification 5 Jul 2020 huiyegit/APLC_XLNet/code/pytorch_transformers/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
A Simple Language Model for Task-Oriented Dialogue 2 May 2020 salesforce/simpletod/models/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong BSD-3-Clause (permissive)
POINTER: Constrained Progressive Text Generation via Insertion-based Generative Pre-training 1 May 2020 dreasysnail/POINTER/pytorch_transformers/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training 1 May 2020 linjieli222/HERO/model/modeling_utils.py 57947ced49b189c3 unverified MIT recorded; this copy not marked cleared · pointer only
VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification 12 Apr 2020 Louis-udm/VGCN-BERT/old_version/pytorch_pretrained_bert/modeling.py 393af350cd7381f6 unverified MIT (permissive)
Parsing as Pretraining 5 Feb 2020 huggingface/pytorch-pretrained-BERT/src/transformers/pytorch_utils.py 24ece331635f4b38 unverified Apache-2.0 recorded; this copy not marked cleared · pointer only
On the Relationship between Self-Attention and Convolutional Layers 8 Nov 2019 epfml/attention-cnn/models/bert.py 2f516ae7fc833c82 unverified Apache-2.0 (permissive)
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations 2 Nov 2019 SVAIGBA/TwASP/pytorch_pretrained_bert/modeling.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders 25 Oct 2019 samirsahoo007/Audio-and-Speech-Processing/mockingjay/model.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations 26 Sep 2019 Soikonomou/albert_final/src/model/ALBERT/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong Apache-2.0 (permissive)
Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering 9 Sep 2019 DecstionBack/AAAI_2020_CommonsenseQA/pytorch_transformers/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong Apache-2.0 (permissive)
XLNet: Generalized Autoregressive Pretraining for Language Understanding 19 Jun 2019 samwisegamjeee/pytorch-transformers/pytorch_transformers/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong Apache-2.0 (permissive)
Evaluating Protein Transfer Learning with TAPE 19 Jun 2019 songlab-cal/tape/tape/models/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong BSD-3-Clause (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 Impavidity/relogic/relogic/logickit/inference/modeling.py f4f4879066931500 ran · our draft was wrong MIT (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 andi611/Mockingjay-Speech-Representation/mockingjay/model.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
arXiv:aaai_5722 microsoft/Distilled-Sentence-Embedding/pytorch_pretrained_bert/modeling.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
arXiv:2024.findings-naacl.32 SnowYJ/sem_syn_separation/optimus_separate_graph_sem_syntax_fuse_gpt2/pytorch_transformers/modeling_utils.py d30d6c3098df2c42 ran · our draft was wrong MIT (permissive)
arXiv:2023.acl-long.264 DAMO-NLP-SG/MVCR/src/pytorch_utils.py 763d53d145dbacb5 unverified MIT recorded; this copy not marked cleared · pointer only
arXiv:2021.emnlp-main.154 Hazelsuko07/TextHide/transformers_hide/modeling_utils.py b3504e72ce1153fe ran 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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