{"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/spherical-dist-loss","entry":"spherical_dist_loss","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":6,"n_papers_ran":3,"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":2,"n_places":6,"n_places_pointer_only":3,"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":"2407.00788","paper":"/paper/instantstyle-plus-style-transfer-with-content","title":"InstantStyle-Plus: Style Transfer with Content-Preserving in Text-to-Image Generation","date":"2024-06-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"instantx-research/instantstyle-plus","path":"pipeline_controlnet_sd_xl_img2img.py","file_url":"https://github.com/instantx-research/instantstyle-plus/blob/HEAD/pipeline_controlnet_sd_xl_img2img.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"eaea2e0cbf2754c5","mcp_get_code":{"code_sha256":"eaea2e0cbf2754c5"}},{"arxiv_id":"2406.04312","paper":"/paper/reno-enhancing-one-step-text-to-image-models","title":"ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization","date":"2024-06-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"salesforce/DOODL","path":"doodl.py","file_url":"https://github.com/salesforce/DOODL/blob/HEAD/doodl.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"216e276b9fb00d10","mcp_get_code":{"code_sha256":"216e276b9fb00d10"}},{"arxiv_id":"2302.11797","paper":"/paper/region-aware-diffusion-for-zero-shot-text","title":"Region-Aware Diffusion for Zero-shot Text-driven Image Editing","date":"2023-02-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"code_sha256_prefix":"36a34f4a30080b93","mcp_get_code":{"code_sha256":"36a34f4a30080b93"}},{"arxiv_id":"2211.16582","paper":"/paper/sinddm-a-single-image-denoising-diffusion","title":"SinDDM: A Single Image Denoising Diffusion Model","date":"2022-11-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"fallenshock/SinDDM","path":"text2live_util/util.py","file_url":"https://github.com/fallenshock/SinDDM/blob/HEAD/text2live_util/util.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3e32294ed366a148","mcp_get_code":{"code_sha256":"3e32294ed366a148"}},{"arxiv_id":"2112.10752","paper":"/paper/high-resolution-image-synthesis-with-latent","title":"High-Resolution Image Synthesis with Latent Diffusion Models","date":"2021-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yangling0818/contextdiff","path":"ContextDiff_image/diffusers/examples/community/clip_guided_stable_diffusion.py","file_url":"https://github.com/yangling0818/contextdiff/blob/HEAD/ContextDiff_image/diffusers/examples/community/clip_guided_stable_diffusion.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"36a34f4a30080b93","mcp_get_code":{"code_sha256":"36a34f4a30080b93"}},{"arxiv_id":"2105.05233","paper":"/paper/diffusion-models-beat-gans-on-image-synthesis","title":"Diffusion Models Beat GANs on Image Synthesis","date":"2021-05-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"afiaka87/clip-guided-diffusion","path":"cgd/losses.py","file_url":"https://github.com/afiaka87/clip-guided-diffusion/blob/HEAD/cgd/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5bd6891b5cc4506d","mcp_get_code":{"code_sha256":"5bd6891b5cc4506d"}}]}