{"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/prepare-latent-image-ids","entry":"prepare_latent_image_ids","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":5,"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":3,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":1,"by_status":{"ran_honours":1,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":2},"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":"2607.18091","paper":"/paper/arxiv-2607-18091","title":"SciForma: Structure-Faithful Generation of Scientific Diagrams","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"microsoft/SciForma","path":"sciforma/utils/model_utils.py","file_url":"https://github.com/microsoft/SciForma/blob/HEAD/sciforma/utils/model_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b1595304e6ce5b67","mcp_get_code":{"code_sha256":"b1595304e6ce5b67"}},{"arxiv_id":"2605.08354","paper":"/paper/arxiv-2605-08354","title":"Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":null,"path":"","file_url":null,"status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"4080cb55d923dfba","mcp_get_code":{"code_sha256":"4080cb55d923dfba"}},{"arxiv_id":"2601.00423","paper":"/paper/arxiv-2601-00423","title":"E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"shengjun-zhang/VisualGRPO","path":"other_algorithms/dancegrpo_train_grpo_flux.py","file_url":"https://github.com/shengjun-zhang/VisualGRPO/blob/HEAD/other_algorithms/dancegrpo_train_grpo_flux.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"4080cb55d923dfba","mcp_get_code":{"code_sha256":"4080cb55d923dfba"}},{"arxiv_id":"2507.15249","paper":null,"title":"arXiv:2507.15249","date":null,"month_inferred_from_arxiv_id":"2025-07","title_source":null,"repo":"Monalissaa/FreeCus","path":"flux_utils.py","file_url":"https://github.com/Monalissaa/FreeCus/blob/HEAD/flux_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"aaf4f9bc7a90c80c","mcp_get_code":{"code_sha256":"aaf4f9bc7a90c80c"}},{"arxiv_id":"2505.07818","paper":"/paper/dancegrpo-unleashing-grpo-on-visual","title":"DanceGRPO: Unleashing GRPO on Visual Generation","date":"2025-05-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xuezeyue/dancegrpo","path":"fastvideo/train_grpo_flux.py","file_url":"https://github.com/xuezeyue/dancegrpo/blob/HEAD/fastvideo/train_grpo_flux.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"4080cb55d923dfba","mcp_get_code":{"code_sha256":"4080cb55d923dfba"}}]}