{"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/tuple-product","entry":"tuple_product","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":9,"n_papers_ran":9,"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":3,"n_samples_ran":3,"n_samples_fingerprinted":3,"n_places":9,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":3,"unverified":0},"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":"2608.05471","paper":"/paper/arxiv-2608-05471","title":"A Foundational EDM2-Based Generative Model for High-Resolution Synthetic Fetal Ultrasound Imaging from Open Datasets","date":null,"month_inferred_from_arxiv_id":"2026-08","title_source":"syntology","repo":"xfetus/fetal-ultrasound-edm2","path":"dnnlib/util.py","file_url":"https://github.com/xfetus/fetal-ultrasound-edm2/blob/HEAD/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d0955d86500b69a3","mcp_get_code":{"code_sha256":"d0955d86500b69a3"}},{"arxiv_id":"2509.16447","paper":"/paper/arxiv-2509-16447","title":"Local Mechanisms of Compositional Generalization in Conditional Diffusion","date":null,"month_inferred_from_arxiv_id":"2025-09","title_source":"syntology","repo":"NVlabs/edm2","path":"dnnlib/util.py","file_url":"https://github.com/NVlabs/edm2/blob/HEAD/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d0955d86500b69a3","mcp_get_code":{"code_sha256":"d0955d86500b69a3"}},{"arxiv_id":"2502.14583","paper":"/paper/a-theory-for-conditional-generative-modeling","title":"A Theory for Conditional Generative Modeling on Multiple Data Sources","date":"2025-02-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ml-gsai/multi-source-gm","path":"real_world_experiments/dnnlib/util.py","file_url":"https://github.com/ml-gsai/multi-source-gm/blob/HEAD/real_world_experiments/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d0955d86500b69a3","mcp_get_code":{"code_sha256":"d0955d86500b69a3"}},{"arxiv_id":"2408.13239","paper":"/paper/customcrafter-customized-video-generation","title":"CustomCrafter: Customized Video Generation with Preserving Motion and Concept Composition Abilities","date":"2024-08-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wutao-cs/customcrafter","path":"eval/dnnlib/util.py","file_url":"https://github.com/wutao-cs/customcrafter/blob/HEAD/eval/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"900a8d68bf48579e","mcp_get_code":{"code_sha256":"900a8d68bf48579e"}},{"arxiv_id":"2311.17101","paper":"/paper/robust-diffusion-gan-using-semi-unbalanced","title":"A High-Quality Robust Diffusion Framework for Corrupted Dataset","date":"2023-11-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"VinAIResearch/RDUOT","path":"dnnlib/util.py","file_url":"https://github.com/VinAIResearch/RDUOT/blob/HEAD/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"efd5d4ab788539f4","mcp_get_code":{"code_sha256":"efd5d4ab788539f4"}},{"arxiv_id":"2310.11440","paper":"/paper/evalcrafter-benchmarking-and-evaluating-large","title":"EvalCrafter: Benchmarking and Evaluating Large Video Generation Models","date":"2023-10-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"EvalCrafter/EvalCrafter","path":"metrics/dnnlib/util.py","file_url":"https://github.com/EvalCrafter/EvalCrafter/blob/HEAD/metrics/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"900a8d68bf48579e","mcp_get_code":{"code_sha256":"900a8d68bf48579e"}},{"arxiv_id":"2004.11660","paper":"/paper/disentangled-and-controllable-face-image","title":"Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning","date":"2020-04-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"microsoft/DiscoFaceGAN","path":"dnnlib/util.py","file_url":"https://github.com/microsoft/DiscoFaceGAN/blob/HEAD/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"efd5d4ab788539f4","mcp_get_code":{"code_sha256":"efd5d4ab788539f4"}},{"arxiv_id":"2004.00049","paper":"/paper/in-domain-gan-inversion-for-real-image","title":"In-Domain GAN Inversion for Real Image Editing","date":"2020-03-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"genforce/idinvert","path":"dnnlib/util.py","file_url":"https://github.com/genforce/idinvert/blob/HEAD/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"efd5d4ab788539f4","mcp_get_code":{"code_sha256":"efd5d4ab788539f4"}},{"arxiv_id":"Xia_Rectified_Diffusion_Guidance_for_Conditional_Generation_CVPR_2025_paper","paper":null,"title":"arXiv:Xia_Rectified_Diffusion_Guidance_for_Conditional_Generation_CVPR_2025_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"thuxmf/recfg","path":"dnnlib/util.py","file_url":"https://github.com/thuxmf/recfg/blob/HEAD/dnnlib/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d0955d86500b69a3","mcp_get_code":{"code_sha256":"d0955d86500b69a3"}}]}