Home › Code › collate_batch

collate_batch

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

collate_batch appears in the code Syntology harvested for 14 papers, as 20 distinct code bodies found in 21 places (a place is one code body under one paper). At least one of them ran in 4 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 collate_batch 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 5 of the 20 distinct code bodies named collate_batch; 15 are 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
5ran
15unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 21 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

14 papers shown of 14, newest first; 21 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; 1 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
EdgeFlowerTune: Evaluating Federated LLM Fine-Tuning Under Realistic Edge System Constraints added by Syntology 2026-05 (from id) Edge-Intelligence-Lab/EdgeFlowerTune/standalone/pytorch_alignment/gemma_lora_finetune.py 3fc000375b6144f3 ran no licence file found · pointer only
EdgeFlowerTune: Evaluating Federated LLM Fine-Tuning Under Realistic Edge System Constraints added by Syntology 2026-05 (from id) Edge-Intelligence-Lab/EdgeFlowerTune/standalone/pytorch_alignment/gpt2_full_finetune.py a972e9d8cdab191e ran no licence file found · pointer only
EdgeFlowerTune: Evaluating Federated LLM Fine-Tuning Under Realistic Edge System Constraints added by Syntology 2026-05 (from id) Edge-Intelligence-Lab/EdgeFlowerTune/standalone/pytorch_alignment/gpt2_lora_finetune.py 95bfef07c91ceaca ran no licence file found · pointer only
Hyperdimensional Cross-Modal Alignment of Frozen Language and Image Models for Efficient Image Captioning added by Syntology 2026-02 (from id) Abhishek-Dalvi410/HDFLIM/train_scripts/train_dataloader.py 3fce7eb3771cbc0d unverified MIT (permissive)
Adjustment for Confounding using Pre-Trained Representations 17 Jun 2025 rickmer-schulte/Pretrained-Causal-Adjust/src/data_setup/create_data_imdb.py edbf00ba07cb1a88 unverified MIT (permissive)
Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing 2025-05 (from id) usr922/lipnovo/LIPNovo/novobench/models/imputation_denovo/impnovo_dataloader.py 046e71c75d9ba9b1 ran Apache-2.0 (permissive)
Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment 21 Mar 2025 ImIntheMiddle/EmLoco/social-transmotion/dataset_jrdb.py 1e2df8b59f173163 unverified MIT (permissive)
Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment 21 Mar 2025 ImIntheMiddle/EmLoco/social-transmotion/dataset_jta.py 629a8b333d7cf5ed unverified MIT (permissive)
NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms 25 Feb 2025 ElectricAlexis/NotaGen/pretrain/train-gen.py 380bd92b6ed0913a unverified MIT (permissive)
CLaMP 3: Universal Music Information Retrieval Across Unaligned Modalities and Unseen Languages 2025-02 (from id) sanderwood/clamp3/code/train_clamp3_audio.py ab89c01dfa845956 unverified MIT (permissive)
Multi-Transmotion: Pre-trained Model for Human Motion Prediction 4 Nov 2024 vita-epfl/multi-transmotion/ft_NBA/dataset.py 259e7ffc93d15e00 unverified GPL-3.0 (copyleft) · pointer only
NovoBench: Benchmarking Deep Learning-based De Novo Peptide Sequencing Methods in Proteomics 16 Jun 2024 Westlake-OmicsAI/NovoBench/novobench/models/adanovo/adanovo_dataloader.py 046e71c75d9ba9b1 ran MIT (permissive)
Time Series Diffusion in the Frequency Domain 8 Feb 2024 jonathancrabbe/fourierdiffusion/src/fdiff/utils/dataclasses.py bf025271edf6bc86 ran MIT (permissive)
Transfer learning on large datasets for the accurate prediction of material properties 2023-03 (from id) hyllios/cgat/CGAT/prepare_data.py 204d873b8398e305 unverified MIT (permissive)
Transfer learning on large datasets for the accurate prediction of material properties 2023-03 (from id) hyllios/cgat/CGAT/roost_message.py edbe36714aa4acc4 unverified MIT (permissive)
Materials Representation and Transfer Learning for Multi-Property Prediction 4 Jun 2021 CompRhys/roost/roost/cgcnn/data.py dd79bba4183b8a50 unverified MIT (permissive)
Materials Representation and Transfer Learning for Multi-Property Prediction 4 Jun 2021 CompRhys/roost/roost/pretrain/dist_data.py 560cdc7d3a9d7b34 unverified MIT (permissive)
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry 1 Oct 2019 s-a-malik/inorg-synth-graph/matgps/reaction_graph/data.py 3a1c29a2c34b5263 unverified MIT (permissive)
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry 1 Oct 2019 s-a-malik/inorg-synth-graph/matgps/reaction_graph_actions/data.py 925c15d01ee368e4 unverified MIT (permissive)
arXiv:ijcai2024_0479 dice-group/ROCES/run_nces2_and_roces_incremental.py 2856816c31a098b0 unverified MIT (permissive)
arXiv:ijcai2024_0479 dice-group/ROCES/active_learn_utils.py 0509b4911ded38a6 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