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make_attn

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

make_attn appears in the code Syntology harvested for 22 papers, as 9 distinct code bodies found in 22 places (a place is one code body under one paper). At least one of them ran in 1 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 make_attn 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 1 of the 9 distinct code bodies named make_attn; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
0ran
8unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 22 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

22 papers shown of 22, newest first; 22 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. 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
Inference-Time Scaling for Visual AutoRegressive modeling by Searching Representative Samples added by Syntology 2026-01 (from id) WD7ang/VAR-Scaling/VAR-main/models/basic_vae.py 793c7e2489dd8dfc unverified MIT (permissive)
Conditional Latent Diffusion Models for Zero-Shot Instance Segmentation added by Syntology 2025-08 (from id) DLR-RM/oc-dit/ocdit/models/ocdit.py 7e141c9d5b330940 unverified MIT (permissive)
MVAR: Visual Autoregressive Modeling with Scale and Spatial Markovian Conditioning 19 May 2025 labshuhanggu/mvar/models/basic_vae.py 793c7e2489dd8dfc unverified MIT (permissive)
VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via Iterative Instruction Tuning and Reinforcement Learning 3 Apr 2025 VARGPT-family/VARGPT/vargpt_llava/var_model/models/basic_vae.py 793c7e2489dd8dfc unverified Apache-2.0 (permissive)
Visual Autoregressive Modeling for Image Super-Resolution 31 Jan 2025 qyp2000/varsr/models/basic_vae.py 793c7e2489dd8dfc unverified MIT (permissive)
Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis 5 Dec 2024 FoundationVision/VAR/models/basic_vae.py 793c7e2489dd8dfc unverified MIT (permissive)
M-VAR: Decoupled Scale-wise Autoregressive Modeling for High-Quality Image Generation 15 Nov 2024 oliverrensu/mvar/models/basic_vae.py 793c7e2489dd8dfc unverified no licence file found · pointer only
ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis 11 Nov 2024 leaplabthu/enat/libs/autoencoder.py f97adc1ae5efb785 unverified no licence file found · pointer only
HART: Efficient Visual Generation with Hybrid Autoregressive Transformer 14 Oct 2024 mit-han-lab/hart/hart/modules/networks/basic_vae.py 793c7e2489dd8dfc unverified MIT (permissive)
WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling 29 Aug 2024 jishengpeng/wavtokenizer/decoder/models.py dba3d5f0d0d4a6f2 unverified MIT (permissive)
HAIR: Hypernetworks-based All-in-One Image Restoration 15 Aug 2024 toummHus/HAIR/utils/ResNet.py e6bdfc1df5bf356d unverified no licence file found · pointer only
VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling 2 Aug 2024 daixiangzi/var-clip/models/basic_vae.py 793c7e2489dd8dfc unverified no licence file found · pointer only
Few-shot Defect Image Generation based on Consistency Modeling 1 Aug 2024 ffdd-diffusion/defectdiffu/autoencoder.py f97adc1ae5efb785 unverified no licence file found · pointer only
Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models and Time-Dependent Layer Normalization 13 Jun 2024 qihao067/DiMR/libs/autoencoder.py f97adc1ae5efb785 unverified Apache-2.0 (permissive)
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability 27 May 2024 opendrivelab/vista/vwm/models/diffusion.py df7cb18ec3f78d30 unverified Apache-2.0 (permissive)
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts 18 May 2024 hitsz-tmg/umoe-scaling-unified-multimodal-llms/Uni-MoE-2/decoder/models.py dba3d5f0d0d4a6f2 unverified no licence file found · pointer only
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction 3 Apr 2024 EkaterinaXie/LiteVAR/models/basic_vae.py 793c7e2489dd8dfc unverified MIT (permissive)
Towards Realistic Scene Generation with LiDAR Diffusion Models 31 Mar 2024 hancyran/lidar-diffusion/lidm/modules/diffusion/model_lidm.py 321eebc8c4fd6b54 unverified MIT (permissive)
T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching 21 Feb 2024 nvlabs/t-stitch/dit/autoencoder.py f97adc1ae5efb785 unverified no licence file found · pointer only
Fast Training of Diffusion Models with Masked Transformers 15 Jun 2023 anima-lab/maskdit/autoencoder.py f97adc1ae5efb785 unverified MIT (permissive)
Latent Video Diffusion Models for High-Fidelity Long Video Generation 23 Nov 2022 yingqinghe/lvdm/lvdm/models/modules/aemodules.py ff5ec4cc14b9e9b2 unverified MIT (permissive)
Classifier-Free Diffusion Guidance 26 Jul 2022 g4vrel/DDPM/sample.py fc896cf6190912f4 ran · our draft was wrong 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