{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/data-transform","entry":"data_transform","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":10,"n_papers_ran":6,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":5,"n_samples_ran":2,"n_samples_fingerprinted":1,"n_places":10,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":1,"unverified":3},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2607.17849","paper":"/paper/arxiv-2607-17849","title":"AlphaOracle: Oracle bone script decipherment via human-workflow-inspired deep learning","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"Yuliang-Liu/AlphaOracle","path":"models/Morphological_analysis/OBSD/ddm.py","file_url":"https://github.com/Yuliang-Liu/AlphaOracle/blob/HEAD/models/Morphological_analysis/OBSD/ddm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"1711055882a8cb05","mcp_get_code":{"code_sha256":"1711055882a8cb05"}},{"arxiv_id":"2407.08939","paper":"/paper/lightendiffusion-unsupervised-low-light-image","title":"LightenDiffusion: Unsupervised Low-Light Image Enhancement with Latent-Retinex Diffusion Models","date":"2024-07-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jianghaiscu/lightendiffusion","path":"utils/sampling.py","file_url":"https://github.com/jianghaiscu/lightendiffusion/blob/HEAD/utils/sampling.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1711055882a8cb05","mcp_get_code":{"code_sha256":"1711055882a8cb05"}},{"arxiv_id":"2406.00684","paper":"/paper/deciphering-oracle-bone-language-with","title":"Deciphering Oracle Bone Language with Diffusion Models","date":"2024-06-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"guanhaisu/OBSD","path":"OBS_Diffusion/models/ddm.py","file_url":"https://github.com/guanhaisu/OBSD/blob/HEAD/OBS_Diffusion/models/ddm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1711055882a8cb05","mcp_get_code":{"code_sha256":"1711055882a8cb05"}},{"arxiv_id":"2310.11142","paper":"/paper/bayesdiff-estimating-pixel-wise-uncertainty","title":"BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference","date":"2023-10-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"karrykkk/BayesDiff","path":"ddpm_and_guided/la_train_datasets.py","file_url":"https://github.com/karrykkk/BayesDiff/blob/HEAD/ddpm_and_guided/la_train_datasets.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c4a69cb9142a7670","mcp_get_code":{"code_sha256":"c4a69cb9142a7670"}},{"arxiv_id":"2306.00306","paper":"/paper/low-light-image-enhancement-with-wavelet","title":"Low-Light Image Enhancement with Wavelet-based Diffusion Models","date":"2023-06-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"JianghaiSCU/Diffusion-Low-Light","path":"models/ddm.py","file_url":"https://github.com/JianghaiSCU/Diffusion-Low-Light/blob/HEAD/models/ddm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1711055882a8cb05","mcp_get_code":{"code_sha256":"1711055882a8cb05"}},{"arxiv_id":"2209.04899","paper":"/paper/instruction-driven-history-aware-policies-for","title":"Instruction-driven history-aware policies for robotic manipulations","date":"2022-09-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"guhur/hiveformer","path":"dataset.py","file_url":"https://github.com/guhur/hiveformer/blob/HEAD/dataset.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"272295b2b14c060e","mcp_get_code":{"code_sha256":"272295b2b14c060e"}},{"arxiv_id":"2207.14626","paper":"/paper/restoring-vision-in-adverse-weather","title":"Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models","date":"2022-07-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"igitugraz/weatherdiffusion","path":"models/ddm.py","file_url":"https://github.com/igitugraz/weatherdiffusion/blob/HEAD/models/ddm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1711055882a8cb05","mcp_get_code":{"code_sha256":"1711055882a8cb05"}},{"arxiv_id":"2105.14951","paper":"/paper/snips-solving-noisy-inverse-problems","title":"SNIPS: Solving Noisy Inverse Problems Stochastically","date":"2021-05-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bahjat-kawar/snips_torch","path":"runners/ncsn_runner.py","file_url":"https://github.com/bahjat-kawar/snips_torch/blob/HEAD/runners/ncsn_runner.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c4a69cb9142a7670","mcp_get_code":{"code_sha256":"c4a69cb9142a7670"}},{"arxiv_id":"1803.10704","paper":"/paper/end-to-end-multi-task-learning-with-attention","title":"End-to-End Multi-Task Learning with Attention","date":"2018-03-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"lorenmt/mtan","path":"visual_decathlon/model_wrn_mtan.py","file_url":"https://github.com/lorenmt/mtan/blob/HEAD/visual_decathlon/model_wrn_mtan.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8cb280994b68ba9b","mcp_get_code":{"code_sha256":"8cb280994b68ba9b"}},{"arxiv_id":"1709.04875","paper":"/paper/spatio-temporal-graph-convolutional-networks","title":"Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting","date":"2017-09-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hazdzz/STGCN","path":"script/dataloader.py","file_url":"https://github.com/hazdzz/STGCN/blob/HEAD/script/dataloader.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"LGPL-2.1","inline_ok":false,"code_sha256_prefix":"04b21c4ef1da58f5","mcp_get_code":{"code_sha256":"04b21c4ef1da58f5"}}]}