{"as_of":"2026-08-13T01:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0afe5848cbd1acfd06bf57f87f8fe3b0df04b36476056d62bab0f58dd0471c7a","coverage":[{"denominator":75,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":75,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T14:03:09.764345Z","state":"measured"},{"denominator":77,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":77,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-03T15:41:05.166452Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T15:48:34.980383Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"cited_work":{"arxiv_id":"2412.12594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12594","snapshot_observed_at":"2026-07-03T15:48:34.980383Z","title":"arXiv preprint arXiv:2412.12594 (2024)","venue":null,"work_id":"5392b476-65b2-4954-bc82-51b560d9efff","year":2024},"citing_paper":{"arxiv_id":"2607.00183","last_updated":"2026-06-30T20:57:51Z","snapshot_observed_at":"2026-08-08T16:52:20.031739Z","submitted_at":"2026-06-30T20:57:51Z","title":"DriftScope: Measuring The Hidden Effects of Diffusion Model Adaptation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-02T19:25:12.921892Z"},"links":{"cited_paper":"/paper/2412.12594","citing_paper":"/paper/2607.00183"},"observation_digest":"sha256:f07f8b8b47c5e82b6c4f1599509ef41ba9c88107c505d0e068318d91da610671","observation_id":"03d20edc-5eb3-4627-aa3a-d91068884496","resolution":{"observed_at":"2026-07-02T19:27:18.506649Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"cited_work":{"arxiv_id":"2412.12594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12594","snapshot_observed_at":"2026-07-03T15:48:34.980383Z","title":"arXiv preprint arXiv:2412.12594 (2024)","venue":null,"work_id":"5392b476-65b2-4954-bc82-51b560d9efff","year":2024},"citing_paper":{"arxiv_id":"2607.02284","last_updated":"2026-07-02T15:02:45Z","snapshot_observed_at":"2026-07-07T00:07:42.752664Z","submitted_at":"2026-07-02T15:02:45Z","title":"FlowCIR: Semantic Transport via Flow Matching for Zero-Shot Composed Image Retrieval","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-03T15:41:05.166452Z"},"links":{"cited_paper":"/paper/2412.12594","citing_paper":"/paper/2607.02284"},"observation_digest":"sha256:408c817ad01c0c630d1b9d4293bdb702ea9d0b7998385650522083ce462f41d4","observation_id":"19135a3d-b82c-433b-bd5b-b2e40002504d","resolution":{"observed_at":"2026-07-03T15:48:34.981883Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.12594/citation-record","integrity":"/paper/2412.12594/integrity","json":"/paper/2412.12594/citation-record.json","paper":"/paper/2412.12594"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.152988Z","title":"Zigzag diffusion sampling: The path to success is zigzag, 2024","venue":null,"work_id":"87efda8f-0587-471b-becf-2cf2203ad36d","year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.399437Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d2d23c7b81053679cefa8f6ca39e3f0d68f2a7b3727afe006c90062ca31f7ce6","observation_id":"2787c472-9c5b-4860-b2c7-212e0f99e693","resolution":{"observed_at":"2026-08-11T14:03:11.158246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.136848Z","title":null,"venue":null,"work_id":"98e865cf-4396-41aa-81de-ec1582d7cf58","year":1924},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.405145Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:4080ff7e1a84fedb4184fafa1793b88431ba25ec9402bf7fdf052b4771869b87","observation_id":"6d7d9b2b-933b-4d04-8d36-0a5a46305179","resolution":{"observed_at":"2026-08-11T14:03:11.142185Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-08-07T21:47:08.589400Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-11T14:03:09.410763Z","title":"Stable video diffusion: Scaling latent video diffusion models to large datasets","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.410763Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:07cf91b7c3c75f3d9b7f35c2aa439604ce0227e362fd5723afa76ed7be2188ff","observation_id":"5194e8fa-0c87-4f3a-84a4-67379dd8807a","resolution":{"observed_at":"2026-08-11T14:03:09.410763Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.120794Z","title":"Food-101–mining discriminative components with random forests","venue":null,"work_id":"2f76f899-dc84-457f-8841-789a881b142f","year":2014},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.416406Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:ce3b841c060325952bf6e714d67dda815a028681de36397ab7d52a9bd29ac9a0","observation_id":"9735c07e-75aa-44f8-acbd-189bd018b0b1","resolution":{"observed_at":"2026-08-11T14:03:11.126149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.104905Z","title":"Language models are few-shot learners","venue":null,"work_id":"b1cbdf0b-a8f9-42fe-9717-3e1952243891","year":1901},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.421665Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:7be8ec3bf58b3564f4423c542327219749f40c4d4800f6836b3b7f96b7c761be","observation_id":"fddf145b-91e2-4edf-8a1f-33471aa8c2bf","resolution":{"observed_at":"2026-08-11T14:03:11.109935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.089101Z","title":"Gen- erating visual representations for zero-shot classification","venue":null,"work_id":"0483c4fb-532a-4f13-b175-c33af90e36b5","year":2017},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.426648Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:1a88e00c703e2dbb59b36e55a5e3220b7c225a06b9446267b8f909cfc726a1b3","observation_id":"4d0d83b5-79f9-46f2-8ffa-ed5ba684fba7","resolution":{"observed_at":"2026-08-11T14:03:11.094454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.13224","last_updated":"2023-06-21T12:35:16Z","snapshot_observed_at":"2026-08-12T14:59:56.314045Z","submitted_at":"2022-11-23T18:59:05Z","title":"Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentors","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.13224","snapshot_observed_at":"2026-08-11T14:03:09.432034Z","title":"Peekaboo: Text to image diffusion models are zero-shot segmentors","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.432034Z"},"links":{"cited_paper":"/paper/2211.13224","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:61477754fab892175aea63dc9bd675c660d1dd4fa453272a18d12fe0020cc894","observation_id":"0eaece84-894e-49c7-9246-e40d1ed7925e","resolution":{"observed_at":"2026-08-11T14:03:09.432034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15241","last_updated":"2024-05-21T11:07:58Z","snapshot_observed_at":"2026-08-02T04:16:08.176028Z","submitted_at":"2023-05-24T15:25:19Z","title":"Robust Classification via a Single Diffusion Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15241","snapshot_observed_at":"2026-08-11T14:03:09.437112Z","title":"Robust clas- sification via a single diffusion model","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.437112Z"},"links":{"cited_paper":"/paper/2305.15241","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:f131679bb6d2e2376a7c9de1c4b717e54685436e0b07045ee00846128ff84fbc","observation_id":"b6da548c-7022-4ad2-8c71-4a9b14ef474b","resolution":{"observed_at":"2026-08-11T14:03:09.437112Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.073127Z","title":"Cimpoi, S","venue":null,"work_id":"b2520196-657d-4f52-a0e5-678c2d7614e9","year":2014},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.442054Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:edb84660178afdfa21e345695c314f378fd38602cbc044188e24ac86260c1ffa","observation_id":"fb242144-acdc-430f-a03b-322dc14b6d45","resolution":{"observed_at":"2026-08-11T14:03:11.077892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.057018Z","title":"Text-to-image diffusion mod- els are zero-shot classifiers","venue":null,"work_id":"2b2434fa-c227-4b9a-abf1-5d527f6df0bf","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.446689Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:50fb307fd93f46530206b69f3bded3f870f3064eab43861af0c8b7a199c29770","observation_id":"8c9e3cd6-4657-4b3a-8b0c-e36cc95886b9","resolution":{"observed_at":"2026-08-11T14:03:11.062258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.040521Z","title":"An analysis of single-layer networks in unsupervised feature learning","venue":null,"work_id":"7c06183e-33fb-43a6-8f34-6a00ee4b3949","year":2011},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.451808Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d63836da185c37d77cf90f696d12db26bee1b17a2c62363af9e7a46d84eba891","observation_id":"949d4467-ab47-4a9c-b16e-36e696cc2b36","resolution":{"observed_at":"2026-08-11T14:03:11.045811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.025815Z","title":"Gan- bert: Generative adversarial learning for robust text classifica- tion with a bunch of labeled examples","venue":null,"work_id":"684b8380-820b-4739-af07-b9903aa14ac8","year":2020},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.456914Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:81daac961e66c237b2e843727ac6c0c4f6cc6c253ee335ed99828b2f17e6d39e","observation_id":"c6fff904-94ef-4198-b761-c2f7c2d7f3c8","resolution":{"observed_at":"2026-08-11T14:03:11.030502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:11.010894Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":"0b7a2b82-fdbd-4d9c-9265-3a8d704e24dc","year":2009},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.461776Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d07b6f633d1b2015c85d46d7733b28dd068cd970fa750015e0bfe035ce98c94e","observation_id":"6c2771e2-9d5c-4a99-b30d-1a43a946ed22","resolution":{"observed_at":"2026-08-11T14:03:11.015514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.995273Z","title":"Diffusion models beat gans on image synthesis","venue":null,"work_id":"825a3f52-f4f1-4e7e-af6f-d49998161272","year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.466341Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:22d9c3cba01384648c4183f9946293e075695d5ef13f3320b24fb077ddbfc1ff","observation_id":"0fc6965b-25df-41bd-8719-658267a68c14","resolution":{"observed_at":"2026-08-11T14:03:11.000419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.976459Z","title":"Class prior estimation from positive and unlabeled data","venue":null,"work_id":"7576c14e-ffe6-46a3-bce8-1a44f074b7cb","year":2014},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.470646Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:b52df1921276bbcdddbc5f7875c7d9ed5f00934a28cb75c066788277da3e3577","observation_id":"e3577e98-98b5-40e6-98f1-e2c05e8f4c15","resolution":{"observed_at":"2026-08-11T14:03:10.981633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.959881Z","title":"One-shot learn- ing of object categories","venue":null,"work_id":"8a49a457-2a82-4412-8810-3f656f2fa2bd","year":2006},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.475100Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:a81935a850447dccc68ebc22d9141ad9d3d1a87d968953db8dc979688a4e7761","observation_id":"e77fe65e-74c8-417d-be27-3deb15fca18f","resolution":{"observed_at":"2026-08-11T14:03:10.965034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.944723Z","title":"Initno: Boosting text-to-image diffu- sion models via initial noise optimization","venue":null,"work_id":"08bd1b96-fbe4-4995-b5ba-47a4c7ebe16c","year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.479430Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:46095c27f14afdbca8614a45efb500328bb1eb88da14ea9ab3de7c55e3d1ce80","observation_id":"5a937d1a-e8ec-4f0e-84b8-a63562159449","resolution":{"observed_at":"2026-08-11T14:03:10.949704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.929588Z","title":"Masked autoencoders are scalable vision learners","venue":null,"work_id":"3834448d-0470-469c-a2a3-bce08f4904e3","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.483663Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:eb8445b8fe4bac3a62e30b0063efe34b1af6a3195de63a99c9dba59164bf935a","observation_id":"0db5f390-4448-45aa-8cf2-342f23451908","resolution":{"observed_at":"2026-08-11T14:03:10.934781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.913856Z","title":"Learning deep representations by mutual information estimation and maximization","venue":null,"work_id":"18805022-03d7-40c5-ac15-ec0970108c30","year":2018},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.487978Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:fd9f626ab8236de21d62401999bd068cfcf51fe58ef6690d16ae5356dbf76301","observation_id":"2ca540a4-5ea7-466c-aabf-e28375b3ff87","resolution":{"observed_at":"2026-08-11T14:03:10.918693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.898343Z","title":"Denoising diffu- sion probabilistic models","venue":null,"work_id":"752dcd74-215c-43f0-a25b-47ba4a280c8e","year":2020},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.492341Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:32f72d460ebe05ec1110eb420e0f68105ebd3c62cf87cb9d96cd0b77301246b2","observation_id":"e221b452-4b8a-43db-a780-d5399b87f34f","resolution":{"observed_at":"2026-08-11T14:03:10.903356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02303","last_updated":"2022-10-05T14:41:38Z","snapshot_observed_at":"2026-07-06T13:59:57.800591Z","submitted_at":"2022-10-05T14:41:38Z","title":"Imagen Video: High Definition Video Generation with Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02303","snapshot_observed_at":"2026-08-11T14:03:09.496577Z","title":"Imagen video: High definition video generation with diffusion models.arXiv preprint arXiv:2210.02303, 2022","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.496577Z"},"links":{"cited_paper":"/paper/2210.02303","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:26afa7ac9f7decb47178186fd4574689126ffc11b049ba4bd0f8ccd0fd9d524a","observation_id":"8f0bdda3-0aaf-44f5-81a5-fb6541aa42ed","resolution":{"observed_at":"2026-08-11T14:03:09.496577Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.882824Z","title":"Intriguing properties of generative classifiers","venue":null,"work_id":"3bdd3008-6ab5-4456-ac07-1d0a5278c00c","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.501815Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:94ba5b2c6ce0c32df235a398924ba0fb7605e68d7a787a5b624b166b2ade4728","observation_id":"558ff329-94f6-4c16-9e12-34185fe10188","resolution":{"observed_at":"2026-08-11T14:03:10.888124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.867561Z","title":"Learning discriminative latent attributes for zero- shot classification","venue":null,"work_id":"04b56e9d-aadc-4747-9468-0ba8354feb72","year":2017},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.506536Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:7cc4c601f2195bb4e91865733db9249be59835a6f5d5302129e9ce4ca1f9315c","observation_id":"083c50f9-fd1e-4ed0-b216-bb74d21e5e42","resolution":{"observed_at":"2026-08-11T14:03:10.872505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.852221Z","title":"Diffwave: A versatile diffusion model for audio synthesis","venue":null,"work_id":"f1e867a9-623a-4178-a657-fbf6942eb4bc","year":2020},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.510981Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:c67c3020b09b9ba7e038204c697180615f96539591f7d41bee6eed603afaab5d","observation_id":"a477ee47-6a86-4868-9cb8-7cc995ff4f26","resolution":{"observed_at":"2026-08-11T14:03:10.857142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.836976Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":"50a78861-afd7-47f7-85fb-479965e0e284","year":2009},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.516250Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:87ad7defa0d724734f7dde7e8118196bc5196708213bce09f89687eb5f1e32b6","observation_id":"fbf6a6fb-4e6b-4396-8dd3-b597d32d9dad","resolution":{"observed_at":"2026-08-11T14:03:10.841570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.821914Z","title":"Neural network classification and prior class probabilities","venue":null,"work_id":"b0168ffd-23f8-472d-97a4-a569813f4e71","year":2002},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.520845Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:c6a9f2eb44739305424e972e211514ef0f70c17bc9690e0e9346e98b6e31cda9","observation_id":"a5007408-7381-4957-9791-3fe05eb2283e","resolution":{"observed_at":"2026-08-11T14:03:10.826912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.806976Z","title":"Robust inference via generative classifiers for handling noisy labels","venue":null,"work_id":"062ef8f2-5f61-4159-b037-0aab01119cfe","year":2019},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.525911Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:e1d2bee913985606df0237aac7d9a51fb20cf87d644078cb5a5778529d1e2a1e","observation_id":"22ac649c-4e91-4828-bb33-2d9e63896638","resolution":{"observed_at":"2026-08-11T14:03:10.811703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.791220Z","title":"Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak","venue":null,"work_id":"fdcdc637-7104-4106-a987-1e2972dd884d","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.530375Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:509476d3fdf5a8e742d553a35cd43ee196424b9e56b25ac4c495de7113c05d26","observation_id":"2c0339af-73af-4de0-87f5-5bb64ca41c4c","resolution":{"observed_at":"2026-08-11T14:03:10.796377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.775450Z","title":"Are genera- tive classifiers more robust to adversarial attacks? In Interna- tional Conference on Machine Learning, pages 3804–3814","venue":null,"work_id":"d1735ed9-99d7-4120-8ade-ebdcda2d7caf","year":2019},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.535392Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:c2570f5ca2f7c0558b25a0ac387c174e6e7d31de09bec97e2056ddd7903ba76e","observation_id":"3974ad20-d1b3-4c49-8c17-d35f1590e7a4","resolution":{"observed_at":"2026-08-11T14:03:10.780532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.758297Z","title":"Magic3d: High-resolution text- to-3d content creation","venue":null,"work_id":"ff8e2e57-c27f-4d8c-8833-28f6fd1ce82c","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.539797Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:562e4f0784ae80ac03b5dbe83ba4b95bcc74f7c6ac15117f1deae143835a9145","observation_id":"56ca9bbb-bb70-483b-a3b0-2ea12704fcfe","resolution":{"observed_at":"2026-08-11T14:03:10.763610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:09.544461Z","title":"Alignment of diffusion models: Fundamentals, challenges, and future","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.544461Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:dd7587e61b88cd0d441f2c61ae71f15a55ac73547ca83684edf27ce433656699","observation_id":"1b5c1a01-7ce5-4dfd-bef7-feaeadf6dea8","resolution":{"observed_at":"2026-08-11T14:03:09.544461Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.742150Z","title":"Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps","venue":null,"work_id":"31b1f0f0-b177-4cc2-9c57-49f79fe48900","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.549067Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:a20f78f0cfc2281a26404fc96c87a84d0275357e4e2652844491538a253b757f","observation_id":"0c90fa59-7137-4516-9ed0-365873aab88f","resolution":{"observed_at":"2026-08-11T14:03:10.747320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.01095","last_updated":"2025-05-19T07:56:56Z","snapshot_observed_at":"2026-07-29T20:17:21.488997Z","submitted_at":"2022-11-02T13:14:30Z","title":"DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.01095","snapshot_observed_at":"2026-08-11T14:03:09.553971Z","title":"Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.553971Z"},"links":{"cited_paper":"/paper/2211.01095","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:32729bed4f23be55a1fbf9ad9d53eedd96cb0b39654afdb7fd287b3ebeaebc82","observation_id":"79918983-afad-4e12-b82f-915d4813d51f","resolution":{"observed_at":"2026-08-11T14:03:09.553971Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.726423Z","title":"Generative classifiers as a basis for trustwor- thy image classification","venue":null,"work_id":"ee762fe2-658f-49e4-9532-91f8f7996064","year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.559339Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:20797a790168b01771349b35f0e7465738b06c90cc59446e4a6d8637ccc4c9c5","observation_id":"1ac522ec-d0e2-4a55-8db3-eae540d396d0","resolution":{"observed_at":"2026-08-11T14:03:10.731473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.709579Z","title":"Costa: Co-occurrence statistics for zero-shot classification","venue":null,"work_id":"7d397c35-c46c-409e-91fb-abe6c4d005dc","year":2014},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.564617Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d3c0ef67da3a4cf915bc45a2eae329b0ad023d0de24f5f8e504b07d7cccba614","observation_id":"5e0e5393-736e-4a3a-9145-50d33214cdf1","resolution":{"observed_at":"2026-08-11T14:03:10.715079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.692286Z","title":"On discriminative vs","venue":null,"work_id":"aa06db43-6278-477d-82ee-aa5707a931bc","year":2001},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.569647Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:fca44796313a1c88a110c8183d91efa6bca00c4fda30bcdacb6de35247eee00e","observation_id":"68e96b1f-fe39-4e22-bf1a-1c72e04c2e33","resolution":{"observed_at":"2026-08-11T14:03:10.698089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10741","last_updated":"2022-03-08T18:18:49Z","snapshot_observed_at":"2026-08-07T12:21:17.790675Z","submitted_at":"2021-12-20T18:42:55Z","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.10741","snapshot_observed_at":"2026-08-11T14:03:09.574430Z","title":"Glide: Towards photorealistic image generation and editing with text-guided diffusion models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.574430Z"},"links":{"cited_paper":"/paper/2112.10741","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:3e663aa33a8d202d238586b1170e6eabcc49dd26ea997a2ffdeb89f1d3f475ab","observation_id":"4d57b6a1-6025-44e3-9fcf-6ae94cd9b05a","resolution":{"observed_at":"2026-08-11T14:03:09.574430Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.676374Z","title":"Glide: Towards photorealistic image gen- eration and editing with text-guided diffusion models","venue":null,"work_id":"7dc359fe-391c-44c4-abd2-1f22e6e3e26e","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.579652Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:9bd549ca160b58427fc952118c6d81574c68ce6e12f0db987cb1725478ec2e78","observation_id":"31db2ee0-ce7f-4966-817c-8ea8aaaee502","resolution":{"observed_at":"2026-08-11T14:03:10.681540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.658721Z","title":"Automated flower classification over a large number of classes","venue":null,"work_id":"eb441fdd-faa7-4bba-ad5e-b0ad46b62d51","year":2008},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.584690Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:ab015ae40b7986af52fc335317976938b9471f93f0a5cafc66253c116758f834","observation_id":"79047461-ec93-4acd-8d0f-33d600c77343","resolution":{"observed_at":"2026-08-11T14:03:10.663883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.642054Z","title":"Per- vasive label errors in test sets destabilize machine learning benchmarks","venue":null,"work_id":"93707f41-5625-46df-9296-647b71dd69e7","year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.589463Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:dfd5a1c9b6a3bb1970297860d1b3c9977900e136dd75144e4b1e2f9c96a4204e","observation_id":"353ed241-d890-43d0-98f8-edf3bea2f960","resolution":{"observed_at":"2026-08-11T14:03:10.647334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-11T10:12:11.384939Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-11T14:03:09.594565Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.594565Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:0864ba523b5652b5040b25cff13ea85244eb82e40051d30156cc846fbbfc89c4","observation_id":"fb8067ca-822e-4abb-8f01-d3646e4be079","resolution":{"observed_at":"2026-08-11T14:03:09.594565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13875","last_updated":"2024-06-24T20:31:00Z","snapshot_observed_at":"2026-08-12T23:38:51.045531Z","submitted_at":"2024-06-19T22:37:42Z","title":"WATT: Weight Average Test-Time Adaptation of CLIP","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13875","snapshot_observed_at":"2026-08-11T14:03:09.599324Z","title":"Watt: Weight average test-time adaption of clip","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.599324Z"},"links":{"cited_paper":"/paper/2406.13875","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:f19a7643a0ce6d0ad238f590d932b8cb66efd2373a5c300e4df35a7afa487f7e","observation_id":"3af9dfa5-a9e3-4228-90d0-081d39c41705","resolution":{"observed_at":"2026-08-11T14:03:09.599324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.624932Z","title":"Cats and dogs","venue":null,"work_id":"3991cf90-2917-4898-849e-a353727a9bce","year":2012},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.604433Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:4041c81805d5fd12dc6f8e006613f7225447f125118bc430307263294d59a896","observation_id":"d44e0620-b092-42b2-b4b0-0a1501ab32e3","resolution":{"observed_at":"2026-08-11T14:03:10.630607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:09.609459Z","title":"Scalable diffusion models with transformers","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.609459Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:0b5fc1c9fc0075b03fd07f1d8fff2c4d54355b063452976281ce9f2e1d386d4e","observation_id":"f360b13b-b180-4632-966d-18eb02b96361","resolution":{"observed_at":"2026-08-11T14:03:09.609459Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.01952","last_updated":"2023-07-04T23:04:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-04T23:04:57Z","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.01952","snapshot_observed_at":"2026-08-11T14:03:09.614802Z","title":"Sdxl: Improving latent diffusion models for high-resolution image synthesis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.614802Z"},"links":{"cited_paper":"/paper/2307.01952","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:9c39556fd0955aa5ad3b59615316f23b3657fe5773a3d902df3eaea94702d844","observation_id":"315ab2b7-cc96-4597-919b-68c65968cd78","resolution":{"observed_at":"2026-08-11T14:03:09.614802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.596805Z","title":"Dreamfusion: Text-to-3d using 2d diffusion","venue":null,"work_id":"554c3206-0850-43db-9542-64f5ddd73bff","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.619776Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:b1d592e8b270e79409305f7522bc0ff9c733213cee9bbd0f19fd9090dc554d54","observation_id":"ade8c2d9-1ea1-4bfd-a572-a513281e49f0","resolution":{"observed_at":"2026-08-11T14:03:10.601591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03739","last_updated":"2024-11-07T03:54:22Z","snapshot_observed_at":"2026-07-06T16:28:22.350574Z","submitted_at":"2023-10-05T17:59:18Z","title":"Aligning Text-to-Image Diffusion Models with Reward Backpropagation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03739","snapshot_observed_at":"2026-08-11T14:03:09.624538Z","title":"Aligning text-to-image diffusion models with reward backpropagation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.624538Z"},"links":{"cited_paper":"/paper/2310.03739","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d31443efe1e324dc646914d2a34759c7dea6dae1c452ab0eff6a7c3a0f576ce7","observation_id":"9aed85d4-585b-4167-8cdb-8a417fa560dc","resolution":{"observed_at":"2026-08-11T14:03:09.624538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.18435","last_updated":"2024-11-29T04:23:28Z","snapshot_observed_at":"2026-08-12T17:18:43.750900Z","submitted_at":"2023-11-30T10:36:19Z","title":"Layered Rendering Diffusion Model for Controllable Zero-Shot Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.18435","snapshot_observed_at":"2026-08-11T14:03:09.629119Z","title":"Layered rendering diffusion model for zero-shot guided image synthesis","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.629119Z"},"links":{"cited_paper":"/paper/2311.18435","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:894858061a00e260889a21692f6356a3bd78f26f1bc40b48080103eb83908561","observation_id":"52a34edc-7bce-4012-ad0e-529dbfcb8d0e","resolution":{"observed_at":"2026-08-11T14:03:09.629119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07509","last_updated":"2023-09-14T08:22:34Z","snapshot_observed_at":"2026-07-06T16:18:21.719024Z","submitted_at":"2023-09-14T08:22:34Z","title":"DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks","version":1},"cited_work":{"arxiv_id":"2309.07509","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.07509","snapshot_observed_at":"2026-08-11T14:03:09.922348Z","title":"DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks","venue":"cs.CV","work_id":"9ee27a53-f616-452a-9720-27acf2138d3a","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.634162Z"},"links":{"cited_paper":"/paper/2309.07509","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:7c51905f12e52493133e171320351cfe274bbc05cde13612ad3519cee22a6b36","observation_id":"962fb6c6-0904-4d99-aa95-d5f90291262e","resolution":{"observed_at":"2026-08-11T14:03:09.930087Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.14041","last_updated":"2024-07-27T14:22:56Z","snapshot_observed_at":"2026-08-12T23:18:58.374622Z","submitted_at":"2024-07-19T05:36:22Z","title":"Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.14041","snapshot_observed_at":"2026-08-11T14:03:09.639328Z","title":"Not all noises are created equally: Diffusion noise selection and optimization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.639328Z"},"links":{"cited_paper":"/paper/2407.14041","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:2202e1a2aefc4236b8dc14eede03a7e9a065686ae3ebfe20dbb6e7952b9ec8b5","observation_id":"708cc96d-7c0c-4694-bb41-af462d0e7053","resolution":{"observed_at":"2026-08-11T14:03:09.639328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:09.644698Z","title":"Language models are unsuper- vised multitask learners","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.644698Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:cf5413aec571877212066db473a368d3c9deb32c5c75ee420b4213e72319f6ad","observation_id":"380531b1-5528-49c8-aef1-beaf49db0779","resolution":{"observed_at":"2026-08-11T14:03:09.644698Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:09.649349Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.649349Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:a145e561aec272cd2e5b333b8d587cd44066770c10b696075a7f976fa02d10e2","observation_id":"684e94f9-4b02-49ce-9a93-b0f10e857d98","resolution":{"observed_at":"2026-08-11T14:03:09.649349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:09.654196Z","title":"Zero-shot text-to-image generation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.654196Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:b3be9dbc331fc381a65f3641985e5a4c056f9bf90956d71d828379a69512ac78","observation_id":"5cd3f589-5544-48af-815c-6aad5085756e","resolution":{"observed_at":"2026-08-11T14:03:09.654196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.06125","snapshot_observed_at":"2026-08-11T14:03:09.659060Z","title":"Hierarchical text-conditional image genera- tion with clip latents","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.659060Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:9c31d12cbd8ea459dd701ef8fd35cbcecd5907f6540b21f2568930324da0ea43","observation_id":"2301333c-a60d-40c6-8432-8713b8b38fd2","resolution":{"observed_at":"2026-08-11T14:03:09.659060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.550266Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"8c1eca4e-0081-4f4c-8bf9-67c05fe227c5","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.664210Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:cf83615516a073b7d4d5b8dcfdce36756561e60454d88f7d3ea1ff6af48dca31","observation_id":"17a1749e-18b5-4407-9b47-8df08369c45a","resolution":{"observed_at":"2026-08-11T14:03:10.555104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.533886Z","title":"Pho- torealistic text-to-image diffusion models with deep language understanding","venue":null,"work_id":"b0d1de3c-83e5-4280-96c5-242559deac3d","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.668904Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:7dca080eba12e267c162d3173eb6b2c62a65e868e9cc7b556ac01bc5516215ad","observation_id":"4cc5cd4e-bfab-4591-ae4c-d7fddfff5f5f","resolution":{"observed_at":"2026-08-11T14:03:10.539132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17042","last_updated":"2023-11-28T18:53:24Z","snapshot_observed_at":"2026-08-11T01:14:10.111824Z","submitted_at":"2023-11-28T18:53:24Z","title":"Adversarial Diffusion Distillation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17042","snapshot_observed_at":"2026-08-11T14:03:09.673889Z","title":"Adversarial diffusion distillation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.673889Z"},"links":{"cited_paper":"/paper/2311.17042","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:5061edc3585e29a2872e23724152deda565868bba54adf2b7dc0db1d808759f4","observation_id":"21c5948a-9ea2-4b2e-8aeb-018d50995422","resolution":{"observed_at":"2026-08-11T14:03:09.673889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.516682Z","title":"Uncertainty-aware deep classifiers using generative models","venue":null,"work_id":"df1ac795-9be3-44d7-839d-23d76b9465a3","year":2020},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.678851Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:862a03797347033fffb79e505377d335c289c96ea830cb939b5ba546891390b1","observation_id":"9fd32a02-071e-47b2-b4f1-e13deeaa6208","resolution":{"observed_at":"2026-08-11T14:03:10.522158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04171","last_updated":"2024-10-08T03:24:10Z","snapshot_observed_at":"2026-08-12T22:30:07.770294Z","submitted_at":"2024-10-05T14:33:28Z","title":"IV-Mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04171","snapshot_observed_at":"2026-08-11T14:03:09.683940Z","title":"Iv-mixed sampler: Leveraging image diffu- sion models for enhanced video synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.683940Z"},"links":{"cited_paper":"/paper/2410.04171","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:3604b62443619d1e89dd9e4c5b40086a8efc04a84be1ffff21c86aec464ac51f","observation_id":"a44b70fd-2a31-4c19-bfb4-a39018ac4b57","resolution":{"observed_at":"2026-08-11T14:03:09.683940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.500476Z","title":"An analysis of variance test for normality (complete samples)","venue":null,"work_id":"55b6522d-56e5-494b-9f70-b226990094d4","year":1965},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.689368Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:729644ceb40927ee63a2bbdb5e52010373363c68b091a1275f97fb79683e74e6","observation_id":"8adc2084-ed4a-456d-bcee-b9198f428d63","resolution":{"observed_at":"2026-08-11T14:03:10.505561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:09.694442Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.694442Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:824c7393d1c71fe540e7fced905288bddfb69f88c28b831f8b715b350dd60343","observation_id":"bcc7344c-76a4-4e0c-8975-303c7bcad205","resolution":{"observed_at":"2026-08-11T14:03:09.694442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.473875Z","title":"Generative modeling by estimating gradients of the data distribution","venue":null,"work_id":"63f57e3a-edac-4ba3-86f9-2dd3f425c655","year":2019},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.699535Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:1fc635a88a4bdcbae1c51b62740c10d0932481be66011a2e19e1842f53e15bd3","observation_id":"dcc6adc0-0955-4067-9057-01a4b81fb10d","resolution":{"observed_at":"2026-08-11T14:03:10.479342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.457825Z","title":"Class- incremental learning with generative classifiers","venue":null,"work_id":"8ad83579-76f4-4452-8f67-2c1b2d64ae35","year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.704765Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:cb2f5a84519a3f82a06ad91b48c316394683c4c9061d3d4f6cea125efd26514c","observation_id":"0faba622-d879-4233-9b79-404f0fb200ad","resolution":{"observed_at":"2026-08-11T14:03:10.462515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.442024Z","title":"Diffusion model align- ment using direct preference optimization","venue":null,"work_id":"fbd56bec-890d-41e5-bdda-e41a4e1569b1","year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.709804Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:0360745f80679c8855321ae18f93b9594ff40c936754cd4ce9284d50406e143d","observation_id":"ef78446a-6ceb-43d2-a7d6-8ff4658e9709","resolution":{"observed_at":"2026-08-11T14:03:10.447393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.426244Z","title":"A survey of zero-shot learning: Settings, methods, and ap- plications","venue":null,"work_id":"1a7a0273-1041-4888-aa67-7ae696382b29","year":2019},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.714692Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:779e3e27e47bd355e0ea96a229f4a8848d7989bfe4099340b5447b51889ac6e0","observation_id":"53ac6bfc-7f24-4eec-b2e6-1a722217c218","resolution":{"observed_at":"2026-08-11T14:03:10.431184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01652","last_updated":"2022-02-08T20:26:45Z","snapshot_observed_at":"2026-08-10T07:52:08.606999Z","submitted_at":"2021-09-03T17:55:52Z","title":"Finetuned Language Models Are Zero-Shot Learners","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.01652","snapshot_observed_at":"2026-08-11T14:03:09.719748Z","title":"Finetuned language models are zero-shot learners","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.719748Z"},"links":{"cited_paper":"/paper/2109.01652","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:14fadc6b366f4a6c829eac7a344b908e8b0941f5e6e255ad66d894d105b4776f","observation_id":"0776bae2-ca5e-4201-a5e3-3314f7df9462","resolution":{"observed_at":"2026-08-11T14:03:09.719748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.409810Z","title":"Robust fine-tuning of zero-shot models","venue":null,"work_id":"3054b4f9-c947-4a35-b02d-ff88c08ef53f","year":2022},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.725397Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:12d42b8c4136bcc804e001944282cccefdd864ee6a16ffc537ca0511aee78540","observation_id":"a99d50b9-3e57-4917-bbe2-5c7bf85c59c8","resolution":{"observed_at":"2026-08-11T14:03:10.415603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.392973Z","title":"Latent embed- dings for zero-shot classification","venue":null,"work_id":"4f3aab79-bdf1-45af-bb09-40cef7454cd1","year":2016},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.730824Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:cd77f68550e9c727f77895808ca02caa61da26e39816ff2f8a30ac3d894be1e3","observation_id":"07b2cbf5-37d3-4bb3-a0c3-23155bee8132","resolution":{"observed_at":"2026-08-11T14:03:10.398390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.375809Z","title":"Dream3d: Zero- shot text-to-3d synthesis using 3d shape prior and text-to- image diffusion models","venue":null,"work_id":"268cf97c-c5b4-432c-8f56-a78c756347f3","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.735691Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:ba7e00e31f55540b31e8333ee5fc89c472811be3c052d177071050221b908846","observation_id":"fa190528-7e57-4ff7-b3d9-9f536cea9a12","resolution":{"observed_at":"2026-08-11T14:03:10.380930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.359397Z","title":"Diffsound: Discrete diffusion model for text-to-sound generation","venue":null,"work_id":"731eb8ae-7d9b-4a59-8f68-f9d898bb4bde","year":null},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.740693Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d9a0d1422facc2822f6dec154622a7cd80765cc3cf58bd10bbfd6d780e00d135","observation_id":"78c569e4-d1bd-4a81-9fdd-ae4b48f99446","resolution":{"observed_at":"2026-08-11T14:03:10.364507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.342470Z","title":"Diffusion models: A comprehensive survey of methods and applications","venue":null,"work_id":"db133544-becd-41ce-8bd0-54b6be659d03","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.745577Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:627e66e8a1364a2fc6bac8c23d1d6be3ea79653c8fdaff1fcb0201e0c6972ff2","observation_id":"61c2f545-6d1f-49e2-9ebd-2fa1dc968cfd","resolution":{"observed_at":"2026-08-11T14:03:10.347280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.327424Z","title":"Zero-shot classification with discriminative semantic representation learning","venue":null,"work_id":"d7718884-3e7f-474e-b99b-481a8d18ea73","year":2017},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.750285Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:acce42112408f35937cf7fc4c009ea4acca0b3fd8d251964bc3876ae0b8775b2","observation_id":"edee1427-655a-4bca-82a0-e455a28c99e8","resolution":{"observed_at":"2026-08-11T14:03:10.332264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:03:10.311287Z","title":"Revisiting discriminative vs","venue":null,"work_id":"666d7938-9e4e-4e8d-accd-4703702cbb5c","year":2023},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.754883Z"},"links":{"citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:24bac7565eacf0b8b749e907cd41f5be5289a8e90c9b180a00dde5f00979460f","observation_id":"f223504e-d4ba-4671-96f8-0f63c2bc3095","resolution":{"observed_at":"2026-08-11T14:03:10.316704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.09502","last_updated":"2025-07-17T03:40:22Z","snapshot_observed_at":"2026-08-12T20:32:44.864278Z","submitted_at":"2024-11-14T15:13:13Z","title":"Golden Noise for Diffusion Models: A Learning Framework","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.09502","snapshot_observed_at":"2026-08-11T14:03:09.759434Z","title":"Golden noise for diffusion models: A learning framework","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.759434Z"},"links":{"cited_paper":"/paper/2411.09502","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d99d3cf72b63a22ff475ca0c4754170fd4528d430e4698abfc47a02a67554b1d","observation_id":"ce1e653f-8bba-4275-ac1a-7b1195875d73","resolution":{"observed_at":"2026-08-11T14:03:09.759434Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.00473","last_updated":"2021-12-11T11:51:43Z","snapshot_observed_at":"2026-07-06T11:53:31.073250Z","submitted_at":"2021-10-01T15:05:33Z","title":"Score-Based Generative Classifiers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.00473","snapshot_observed_at":"2026-08-11T14:03:09.764345Z","title":"Score-based generative classifiers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-11T14:03:09.764345Z"},"links":{"cited_paper":"/paper/2110.00473","citing_paper":"/paper/2412.12594"},"observation_digest":"sha256:d85dd54d2f2afc9a75796da337875669b59eb6486afa56f738501b99a1f70735","observation_id":"e941c53e-61cf-465e-b8bc-2c451ea4e627","resolution":{"observed_at":"2026-08-11T14:03:09.764345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.12594","last_updated":"2024-12-17T06:50:23Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T13:53:39.897137Z","submitted_at":"2024-12-17T06:50:23Z","title":"A Simple and Efficient Baseline for Zero-Shot Generative Classification"},"reference_resolution":{"displayed":75,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":1,"verified_fuzzy":49},"total_outbound_references":75},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2412.12594."}