{"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/gblock","entry":"GBlock","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":8,"n_papers_ran":4,"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":8,"n_samples_ran":4,"n_samples_fingerprinted":2,"n_places":8,"n_places_pointer_only":6,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":4,"unverified":4},"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":"2210.14461","paper":"/paper/tpfnet-a-novel-text-in-painting-transformer","title":"TPFNet: A Novel Text In-painting Transformer for Text Removal","date":"2022-10-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"candlelabai/tpfnet","path":"model.py","file_url":"https://github.com/candlelabai/tpfnet/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3c6194978eb992a5","mcp_get_code":{"code_sha256":"3c6194978eb992a5"}},{"arxiv_id":"2206.09104","paper":"/paper/score-guided-intermediate-layer-optimization","title":"Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems","date":"2022-06-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"giannisdaras/ilo","path":"ilo_biggan.py","file_url":"https://github.com/giannisdaras/ilo/blob/HEAD/ilo_biggan.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1aa1a38d61f04f79","mcp_get_code":{"code_sha256":"1aa1a38d61f04f79"}},{"arxiv_id":"2204.04950","paper":"/paper/commonality-in-natural-images-rescues-gans","title":"Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data","date":"2022-04-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"FriedRonaldo/Primitives-PS","path":"cifar/diffAug-cifar-posttrain/BigGAN.py","file_url":"https://github.com/FriedRonaldo/Primitives-PS/blob/HEAD/cifar/diffAug-cifar-posttrain/BigGAN.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0a15eca7a1364237","mcp_get_code":{"code_sha256":"0a15eca7a1364237"}},{"arxiv_id":"2110.10139","paper":"/paper/chunked-autoregressive-gan-for-conditional-1","title":"Chunked Autoregressive GAN for Conditional Waveform Synthesis","date":"2021-10-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"descriptinc/cargan","path":"cargan/model/gantts/generator.py","file_url":"https://github.com/descriptinc/cargan/blob/HEAD/cargan/model/gantts/generator.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2213ef2c811eb16f","mcp_get_code":{"code_sha256":"2213ef2c811eb16f"}},{"arxiv_id":"2102.06696","paper":"/paper/efficient-conditional-gan-transfer-with","title":"Efficient Conditional GAN Transfer with Knowledge Propagation across Classes","date":"2021-02-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mshahbazi72/cGANTransfer","path":"BigGAN.py","file_url":"https://github.com/mshahbazi72/cGANTransfer/blob/HEAD/BigGAN.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9e12416d71f52bb1","mcp_get_code":{"code_sha256":"9e12416d71f52bb1"}},{"arxiv_id":"2006.08265","paper":"/paper/gs-wgan-a-gradient-sanitized-approach-for","title":"GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators","date":"2020-06-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"DingfanChen/GS-WGAN","path":"source/models.py","file_url":"https://github.com/DingfanChen/GS-WGAN/blob/HEAD/source/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"53f434fe0e4156d9","mcp_get_code":{"code_sha256":"53f434fe0e4156d9"}},{"arxiv_id":"2006.03575","paper":"/paper/end-to-end-adversarial-text-to-speech","title":"End-to-End Adversarial Text-to-Speech","date":"2020-06-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yanggeng1995/EATS","path":"models/model.py","file_url":"https://github.com/yanggeng1995/EATS/blob/HEAD/models/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"013522fc606d3e1c","mcp_get_code":{"code_sha256":"013522fc606d3e1c"}},{"arxiv_id":"1812.04948","paper":"/paper/a-style-based-generator-architecture-for","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","date":"2018-12-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Aruie/Aru_StyleGAN","path":"model/Stylegan.py","file_url":"https://github.com/Aruie/Aru_StyleGAN/blob/HEAD/model/Stylegan.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"98cc061f10a2246c","mcp_get_code":{"code_sha256":"98cc061f10a2246c"}}]}