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TokenEmbedding

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

TokenEmbedding appears in the code Syntology harvested for 11 papers, as 18 distinct code bodies found in 18 places (a place is one code body under one paper). At least one of them ran in 10 of the papers; 3 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 TokenEmbedding 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 17 of the 18 distinct code bodies named TokenEmbedding; 1 is unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
17ran
1unverified
3fingerprinted

Licence is a property of each copy, so it is counted per place: 6 of the 18 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

11 papers shown of 11, newest first; 18 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. 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
SPOTR: Spatio-temporal Pooling One-Token Reconstruction for Universal Physiological Signal Self-supervised Learning added by Syntology 2026-06 (from id) PKUDigitalHealth/HeartLang/modeling_pretrain.py aae10c401a510e87 ran · metamorphic tier: deterministic MIT (permissive)
UniTS: A Unified Multi-Task Time Series Model 29 Feb 2024 thuml/Time-Series-Library/models/TimeMixer.py 588a4a8475ed63a0 ran · metamorphic tier: deterministic MIT (permissive)
Learning Structure-Aware Representations of Dependent Types 3 Feb 2024 konstantinoskokos/quill/src/quill/nn/model.py 29f310dfa3baa3c0 unverified no licence file found · pointer only
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction 19 Jan 2023 BUAABIGSCity/PDFormer/libcity/model/traffic_flow_prediction/PDFormer.py 77819d970a28b38d ran MIT (permissive)
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting 15 Dec 2022 BeBeYourLove/TDformer/model/TDformer.py a06a4f88ba660a18 ran · metamorphic tier: invariant fingerprinted no licence file found · pointer only
Scene Text Recognition with Permuted Autoregressive Sequence Models 14 Jul 2022 baudm/parseq/strhub/models/parseq/model.py 7d1582338e324271 ran Apache-2.0 (permissive)
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting 24 Jun 2021 thuml/autoformer/models/Autoformer.py 7c956e353b5b9e7c ran MIT (permissive)
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting 14 Dec 2020 martinwhl/Informer-PyTorch-Lightning/models/informer/model.py b27ba004293a09c9 ran · metamorphic tier: deterministic Apache-2.0 (permissive)
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting 14 Dec 2020 larsbentsen/fftransformer/models/Informer.py 5757cd5e31be6f96 ran · metamorphic tier: deterministic no licence file found · pointer only
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting 14 Dec 2020 AndrzejMiskow/TradeAI/prediction_service/transformers/models.py ffff571f678f5301 ran · metamorphic tier: deterministic MIT (permissive)
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting 14 Dec 2020 tianhai123/Informer-Tensorflow/models/model.py db188ee2de158d14 ran Apache-2.0 (permissive)
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting 14 Dec 2020 zhouhaoyi/Informer2020/models/model.py 1f7e24f214af5f8f ran · metamorphic tier: invariant fingerprinted Apache-2.0 (permissive)
Longformer: The Long-Document Transformer 10 Apr 2020 AIResearchHub/transformergallery/transformer/longformer.py 0840d53a3e87bbd0 ran · metamorphic tier: deterministic MIT (permissive)
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations 26 Sep 2019 xinyooo/ALBERT4Rec/models/albert_modules/albert.py 80bf93fd89246988 ran · metamorphic tier: deterministic no licence file found · pointer only
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 fanchenyou/transformer-study/transformer_bert_from_scratch_5.py 6ac09cf3d33d9991 ran · metamorphic tier: deterministic no licence file found · pointer only
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 codertimo/BERT-pytorch/bert_pytorch/model/bert.py 5f83a220fada640e ran · metamorphic tier: deterministic Apache-2.0 (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 Linar23/Research_work/nn/embedding/bert.py 19ed76f032cfa56a ran no licence file found · pointer only
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 re-search/DocProduct/keras_bert/bert.py dfc55eabce3cbf08 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".

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