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weight_reduce_loss

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

weight_reduce_loss appears in the code Syntology harvested for 61 papers, as 12 distinct code bodies found in 61 places (a place is one code body under one paper). At least one of them ran in 6 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 weight_reduce_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 3 of the 12 distinct code bodies named weight_reduce_loss; 9 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
1ran · fixture could not drive it
2ran
9unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 17 of the 61 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

61 papers shown of 61, newest first; 61 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 4 papers added by Syntology; 13 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
P-PatchDiff: Progressive Patch Diffusion Models for Low-light Image Enhancement added by Syntology 2026-09 (from id) RuoyuGuo/P-PatchDiff/BasicSR-light/basicsr/losses/loss_util.py 94401022438b2365 unverified no licence file found · pointer only
Joint Geometric and Trajectory Consistency Learning for One-Step Real-World Super-Resolution added by Syntology 2026-02 (from id) Blazedengcy/GTASR/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
When One Moment Isn't Enough: Multi-Moment Retrieval with Cross-Moment Interactions added by Syntology 2025-10 (from id) Zhuo-Cao/QV-M2/blocks/loss.py ce1cd2e06b72b9bf unverified no licence file found · pointer only
Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable Refinement added by Syntology 2025-10 (from id) lyd-2022/Latent-Harmony/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
MODEM: A Morton-Order Degradation Estimation Mechanism for Adverse Weather Image Recovery 23 May 2025 hainuo-wang/modem/basicsr/models/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
Progressive Focused Transformer for Single Image Super-Resolution 26 Mar 2025 labshuhanggu/pft-sr/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Visual Autoregressive Modeling for Image Super-Resolution 31 Jan 2025 qyp2000/varsr/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
Auto-Encoded Supervision for Perceptual Image Super-Resolution 28 Nov 2024 2minkyulee/aesop-auto-encoded-supervision-for-perceptual-image-super-resolution/AESOP/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
MAT: Multi-Range Attention Transformer for Efficient Image Super-Resolution 26 Nov 2024 stella-von/MAT/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
Efficient Video Face Enhancement with Enhanced Spatial-Temporal Consistency 25 Nov 2024 dixin-lab/bfvr-stc/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving 22 Nov 2024 hustvl/diffusiondrive/navsim/agents/diffusiondrive/modules/multimodal_loss.py 0542dd6d4721de5d unverified MIT (permissive)
Unsupervised Modality Adaptation with Text-to-Image Diffusion Models for Semantic Segmentation 29 Oct 2024 XiaRho/MADM/modeling/criterion.py 9a78b68ccf3be3bb unverified no licence file found · pointer only
ECMamba: Consolidating Selective State Space Model with Retinex Guidance for Efficient Multiple Exposure Correction 28 Oct 2024 LowlevelAI/ECMamba/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation 24 Oct 2024 shallowdream204/dreamclear/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Hallo2: Long-Duration and High-Resolution Audio-Driven Portrait Image Animation 10 Oct 2024 fudan-generative-vision/hallo2/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model 24 Aug 2024 chen-rao/vd-diff/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
OAPT: Offset-Aware Partition Transformer for Double JPEG Artifacts Removal 21 Aug 2024 QMoQ/OAPT/oapt/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution 19 Jun 2024 DachunKai/EvTexture/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Blur-aware Spatio-temporal Sparse Transformer for Video Deblurring 11 Jun 2024 huicongzhang/bsstnet/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
Correlation Matching Transformation Transformers for UHD Image Restoration 2 Jun 2024 supersupercong/uhdformer/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model 16 May 2024 yongsongh/irsrmamba/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Learning A Spiking Neural Network for Efficient Image Deraining 10 May 2024 MingTian99/ESDNet/losses.py 91101566c8adc964 ran no licence file found · pointer only
Training Transformer Models by Wavelet Losses Improves Quantitative and Visual Performance in Single Image Super-Resolution 17 Apr 2024 mandalinadagi/wavelettention/wavelettention/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Ship in Sight: Diffusion Models for Ship-Image Super Resolution 27 Mar 2024 luigisigillo/shipinsight/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
D3T: Distinctive Dual-Domain Teacher Zigzagging Across RGB-Thermal Gap for Domain-Adaptive Object Detection 14 Mar 2024 EdwardDo69/D3T/experiment/flir_rgb2thermal/losses.py d5b31a76e797a5de ran · fixture could not drive it Apache-2.0 (permissive)
Activating Wider Areas in Image Super-Resolution 13 Mar 2024 arsenalcheng/mma/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Efficient Image Deblurring Networks based on Diffusion Models 11 Jan 2024 bnm6900030/swintormer/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy 7 Jan 2024 xiangtaokong/mioir/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
Iterative Token Evaluation and Refinement for Real-World Super-Resolution 9 Dec 2023 chaofengc/iter/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields 6 Dec 2023 keloee/maskfield/models/focal_loss.py 0b78c3cf1e82d884 unverified MIT (permissive)
Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration 28 Nov 2023 zhihefang/wf-diff/basicsr/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation 17 Aug 2023 wenxi-yue/surgicalsam/surgicalSAM/loss.py bd54cbe9d9fb8b02 ran MIT (permissive)
Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model 7 Aug 2023 srameo/led/led/losses/loss_util.py 1ba39317ea81871a unverified no licence file found · pointer only
Dual Aggregation Transformer for Image Super-Resolution 7 Aug 2023 zhengchen1999/dat/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Exploiting Diffusion Prior for Real-World Image Super-Resolution 11 May 2023 naagar/art_restoration_dm/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
LMPT: Prompt Tuning with Class-Specific Embedding Loss for Long-tailed Multi-Label Visual Recognition 8 May 2023 richard-peng-xia/LMPT/lmpt/bl.py 8553862254d49840 unverified Apache-2.0 (permissive)
Human Guided Ground-truth Generation for Realistic Image Super-resolution 23 Mar 2023 ChrisDud0257/HGGT/ImageEnhancement/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Recursive Generalization Transformer for Image Super-Resolution 11 Mar 2023 zhengchen1999/RGT/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
LMR: A Large-Scale Multi-Reference Dataset for Reference-based Super-Resolution 9 Mar 2023 wdmwhh/MRefSR/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders 22 Dec 2022 piddnad/ddcolor/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Recurrent Video Restoration Transformer with Guided Deformable Attention 5 Jun 2022 labshuhanggu/mia-vsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
Blueprint Separable Residual Network for Efficient Image Super-Resolution 12 May 2022 xiaom233/bsrn/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution 27 Mar 2022 csjliang/DASR/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
EPNet++: Cascade Bi-directional Fusion for Multi-Modal 3D Object Detection 21 Dec 2021 happinesslz/epnetv2/lib/net/seg_utils.py 9a78b68ccf3be3bb unverified MIT (permissive)
Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection 9 Dec 2021 2gunsu/monocon-pytorch/losses/utils.py d02fb39bb36bc9f7 unverified Apache-2.0 (permissive)
YOLOX: Exceeding YOLO Series in 2021 18 Jul 2021 StephenStorm/YOLOX/yolox/models/VariFocalLoss.py 8553862254d49840 unverified Apache-2.0 (permissive)
PanNuke Dataset Extension, Insights and Baselines 24 Mar 2020 kaiseem/pointnu-net/losses/generalise_focal_loss.py 8553862254d49840 unverified MIT (permissive)
SOLOv2: Dynamic and Fast Instance Segmentation 23 Mar 2020 OpenFirework/pytorch_solov2/modules/solov2.py d5b31a76e797a5de ran · fixture could not drive it no licence file found · pointer only
arXiv:ijcai2024_0081 JPWang-CS/FreqFormer/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
arXiv:aaai_32582 Hankitle/PEIE/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
arXiv:aaai_28514 wenxi-yue/SurgicalSAM/surgicalSAM/loss.py bd54cbe9d9fb8b02 ran MIT (permissive)
arXiv:aaai_28354 W-JG/BPOSR/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
arXiv:aaai_28342 VUT-HFUT/EulerMormer/utils/utils.py 1ba39317ea81871a unverified MIT (permissive)
arXiv:Zheng_Efficient_Video_Super-Resolution_for_Real-time_Rendering_with_Decoupled_G-buffer_Guidance_CVPR_2025_paper sunny2109/RDG/basicsr/losses/loss_util.py 1ba39317ea81871a unverified Apache-2.0 (permissive)
arXiv:Pan_Deep_Discriminative_Spatial_and_Temporal_Network_for_Efficient_Video_Deblurring_CVPR_2023_paper xuboming8/DSTNet/basicsr/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
arXiv:Liao_Multiple_View_Geometry_Transformers_for_3D_Human_Pose_Estimation_CVPR_2024_paper XunshanMan/MVGFormer/lib/core/loss.py 8553862254d49840 unverified Apache-2.0 (permissive)
arXiv:Kong_Efficient_Frequency_Domain-Based_Transformers_for_High-Quality_Image_Deblurring_CVPR_2023_paper kkkls/FFTformer/basicsr/models/losses/loss_util.py 1ba39317ea81871a unverified MIT (permissive)
arXiv:Deng_Harmonious_Teacher_for_Cross-Domain_Object_Detection_CVPR_2023_paper kinredon/Harmonious-Teacher/ht_c2b/losses.py d5b31a76e797a5de ran · fixture could not drive it Apache-2.0 (permissive)
arXiv:Chao_Equivalent_Transformation_and_Dual_Stream_Network_Construction_for_Mobile_Image_CVPR_2023_paper ECNUSR/ETDS/core/losses/loss_util.py 15a380deddc7cb1e unverified Apache-2.0 (permissive)
arXiv:2023.findings-emnlp.517 jyansir/Text2Tree/balanced_loss_utils.py 8553862254d49840 unverified MIT (permissive)
arXiv:136790177 yuhuUSTC/FSDGN/basicsr/losses/loss_util.py 1ba39317ea81871a 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".

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