{"about":{"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.","site":"https://codewithpapers.app","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","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/multimodal-generation/papers/ran/1","list_of":"/task/multimodal-generation","task":"multimodal generation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,18],"of":18,"counts":{"archive_papers_tagged":98,"with_a_code_link":53,"where_syntology_ran_a_sample":18,"not_listed_spam_title":0,"listed":98,"listed_where_code_ran":18,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":17,"every_run_a_failure_of_syntologys_instrument":1,"listed_with_a_run_with_no_instrument_failure":17,"listed_every_run_a_failure_of_syntologys_instrument":1,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/multimodal-generation/papers/ran/1","prev":null,"next":null,"papers":[{"url":"/paper/omnigen2-exploration-to-advanced-multimodal","slug":"omnigen2-exploration-to-advanced-multimodal","title":"OmniGen2: Exploration to Advanced Multimodal Generation","date":"2025-06-23","arxiv_id":"2506.18871","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/omnigen2-exploration-to-advanced-multimodal#ran","syntology_url":"https://syntology.ai/paper/2506.18871","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.18871"}},"official":{"repos":["vectorspacelab/omnigen2"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/muddit-liberating-generation-beyond-text-to","slug":"muddit-liberating-generation-beyond-text-to","title":"Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model","date":"2025-05-29","arxiv_id":"2505.23606","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":1,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/muddit-liberating-generation-beyond-text-to#ran","syntology_url":"https://syntology.ai/paper/2505.23606","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2505.23606"}},"official":{"repos":["m-e-agi-lab/muddit"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/emerging-properties-in-unified-multimodal","slug":"emerging-properties-in-unified-multimodal","title":"Emerging Properties in Unified Multimodal Pretraining","date":"2025-05-20","arxiv_id":"2505.14683","repositories_listed":2,"syntology":{"n":21,"n_ran":19,"n_constructed":0,"n_ran_checked":16,"n_instrument":3,"n_unverified":2,"n_honours":3,"n_violates":0,"n_no_contract":13,"n_pointer_only":3,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 3 honoured, 0 violated, 13 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/emerging-properties-in-unified-multimodal#ran","syntology_url":"https://syntology.ai/paper/2505.14683","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2505.14683"}},"official":null}},{"url":"/paper/crystalformer-rl-reinforcement-fine-tuning","slug":"crystalformer-rl-reinforcement-fine-tuning","title":"CrystalFormer-RL: Reinforcement Fine-Tuning for Materials Design","date":"2025-04-03","arxiv_id":"2504.02367","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/crystalformer-rl-reinforcement-fine-tuning#ran","syntology_url":"https://syntology.ai/paper/2504.02367","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2504.02367"}},"official":{"repos":["deepmodeling/crystalformer"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/omnimamba-efficient-and-unified-multimodal","slug":"omnimamba-efficient-and-unified-multimodal","title":"OmniMamba: Efficient and Unified Multimodal Understanding and Generation via State Space Models","date":"2025-03-11","arxiv_id":"2503.08686","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":2,"n_instrument":5,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 5 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/omnimamba-efficient-and-unified-multimodal#ran","syntology_url":"https://syntology.ai/paper/2503.08686","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.08686"}},"official":{"repos":["hustvl/omnimamba"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/multi-modal-retrieval-augmented-multi-modal","slug":"multi-modal-retrieval-augmented-multi-modal","title":"Multi-modal Retrieval Augmented Multi-modal Generation: A Benchmark, Evaluate Metrics and Strong Baselines","date":"2024-11-25","arxiv_id":"2411.16365","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/multi-modal-retrieval-augmented-multi-modal#ran","syntology_url":"https://syntology.ai/paper/2411.16365","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.16365"}},"official":null}},{"url":"/paper/unifashion-a-unified-vision-language-model","slug":"unifashion-a-unified-vision-language-model","title":"UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation","date":"2024-08-21","arxiv_id":"2408.11305","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":7,"n_instrument":1,"n_unverified":3,"n_honours":1,"n_violates":1,"n_no_contract":5,"n_pointer_only":11,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 1 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unifashion-a-unified-vision-language-model#ran","syntology_url":"https://syntology.ai/paper/2408.11305","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2408.11305"}},"official":{"repos":["xiangyu-mm/unifashion"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/harmonizing-visual-text-comprehension-and","slug":"harmonizing-visual-text-comprehension-and","title":"Harmonizing Visual Text Comprehension and Generation","date":"2024-07-23","arxiv_id":"2407.16364","repositories_listed":1,"syntology":{"n":18,"n_ran":11,"n_constructed":0,"n_ran_checked":7,"n_instrument":4,"n_unverified":7,"n_honours":1,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 4 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/harmonizing-visual-text-comprehension-and#ran","syntology_url":"https://syntology.ai/paper/2407.16364","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.16364"}},"official":{"repos":["bytedance/textharmony"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/pmg-personalized-multimodal-generation-with","slug":"pmg-personalized-multimodal-generation-with","title":"PMG : Personalized Multimodal Generation with Large Language Models","date":"2024-04-07","arxiv_id":"2404.08677","repositories_listed":3,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/pmg-personalized-multimodal-generation-with#ran","syntology_url":"https://syntology.ai/paper/2404.08677","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.08677"}},"official":{"repos":["Suikasxt/PMG"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/minigpt-5-interleaved-vision-and-language","slug":"minigpt-5-interleaved-vision-and-language","title":"MiniGPT-5: Interleaved Vision-and-Language Generation via Generative Vokens","date":"2023-10-03","arxiv_id":"2310.02239","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":2,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/minigpt-5-interleaved-vision-and-language#ran","syntology_url":"https://syntology.ai/paper/2310.02239","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.02239"}},"official":{"repos":["eric-ai-lab/minigpt-5"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/making-llama-see-and-draw-with-seed-tokenizer","slug":"making-llama-see-and-draw-with-seed-tokenizer","title":"Making LLaMA SEE and Draw with SEED Tokenizer","date":"2023-10-02","arxiv_id":"2310.01218","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":2,"n_no_contract":4,"n_pointer_only":11,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 2 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/making-llama-see-and-draw-with-seed-tokenizer#ran","syntology_url":"https://syntology.ai/paper/2310.01218","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.01218"}},"official":{"repos":["ailab-cvc/seed"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/finite-scalar-quantization-vq-vae-made-simple","slug":"finite-scalar-quantization-vq-vae-made-simple","title":"Finite Scalar Quantization: VQ-VAE Made Simple","date":"2023-09-27","arxiv_id":"2309.15505","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":2,"n_no_contract":1,"n_pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 2 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/finite-scalar-quantization-vq-vae-made-simple#ran","syntology_url":"https://syntology.ai/paper/2309.15505","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.15505"}},"official":{"repos":["google-research/google-research"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/dreamllm-synergistic-multimodal-comprehension","slug":"dreamllm-synergistic-multimodal-comprehension","title":"DreamLLM: Synergistic Multimodal Comprehension and Creation","date":"2023-09-20","arxiv_id":"2309.11499","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/dreamllm-synergistic-multimodal-comprehension#ran","syntology_url":"https://syntology.ai/paper/2309.11499","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.11499"}},"official":{"repos":["RunpeiDong/DreamLLM"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/learning-to-generate-semantic-layouts-for","slug":"learning-to-generate-semantic-layouts-for","title":"Learning to Generate Semantic Layouts for Higher Text-Image Correspondence in Text-to-Image Synthesis","date":"2023-08-16","arxiv_id":"2308.08157","repositories_listed":1,"syntology":{"n":17,"n_ran":15,"n_constructed":0,"n_ran_checked":14,"n_instrument":1,"n_unverified":2,"n_honours":4,"n_violates":3,"n_no_contract":7,"n_pointer_only":17,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 4 honoured, 3 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/learning-to-generate-semantic-layouts-for#ran","syntology_url":"https://syntology.ai/paper/2308.08157","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.08157"}},"official":{"repos":["pmh9960/GCDP"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/on-evaluating-adversarial-robustness-of-large","slug":"on-evaluating-adversarial-robustness-of-large","title":"On Evaluating Adversarial Robustness of Large Vision-Language Models","date":"2023-05-26","arxiv_id":"2305.16934","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/on-evaluating-adversarial-robustness-of-large#ran","syntology_url":"https://syntology.ai/paper/2305.16934","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.16934"}},"official":{"repos":["yunqing-me/attackvlm"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/grounding-language-models-to-images-for","slug":"grounding-language-models-to-images-for","title":"Grounding Language Models to Images for Multimodal Inputs and Outputs","date":"2023-01-31","arxiv_id":"2301.13823","repositories_listed":2,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/grounding-language-models-to-images-for#ran","syntology_url":"https://syntology.ai/paper/2301.13823","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2301.13823"}},"official":{"repos":["kohjingyu/fromage"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/multimedia-generative-script-learning-for","slug":"multimedia-generative-script-learning-for","title":"Multimedia Generative Script Learning for Task Planning","date":"2022-08-25","arxiv_id":"2208.12306","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/multimedia-generative-script-learning-for#ran","syntology_url":"https://syntology.ai/paper/2208.12306","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2208.12306"}},"official":{"repos":["EagleW/Multimedia-Generative-Script-Learning-for-Task-Planning"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/continual-and-multi-task-architecture-search","slug":"continual-and-multi-task-architecture-search","title":"Continual and Multi-Task Architecture Search","date":"2019-06-12","arxiv_id":"1906.05226","repositories_listed":1,"syntology":{"n":12,"n_ran":11,"n_constructed":0,"n_ran_checked":10,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":9,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 1 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/continual-and-multi-task-architecture-search#ran","syntology_url":"https://syntology.ai/paper/1906.05226","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.05226"}},"official":{"repos":["ramakanth-pasunuru/CAS-MAS"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}}],"record_sha256":"7dced8123203bd188fd1287ac19a4f617b0a6be4cb940815a135227d0894b41e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}